CN113728294B

CN113728294B - Power consumption control and scheme generation method, device, system and storage medium

Info

Publication number: CN113728294B
Application number: CN201980095638.9A
Authority: CN
Inventors: 奉有泉; 卢毅军; 李栈; 陶原; 赵旭
Original assignee: Alibaba Cloud Computing Ltd
Current assignee: Alibaba Cloud Computing Ltd
Priority date: 2019-09-06
Filing date: 2019-09-06
Publication date: 2023-03-31
Anticipated expiration: 2039-09-06
Also published as: WO2021042368A1; CN113728294A

Abstract

A power control and scheme generation method, equipment, a system and a storage medium abstract power control into a scheme, can dynamically update the power control scheme of each physical equipment or equipment group through artificial intelligence, realize dynamic power control, and can ensure that the power control is accurate to each physical equipment or equipment group, thereby not only improving the accuracy of power control, but also improving the overall energy-saving effect of power control.

Description

Power consumption control and scheme generation method, device, system and storage medium

Technical Field

The present application relates to the field of data center technologies, and in particular, to a method, a device, a system, and a storage medium for power consumption control and scheme generation.

Background

With the development of cloud computing technology, various Data Centers (DCs) are continuously deployed, and the problem of energy consumption of the Data centers is increasingly highlighted. Various power consumption control methods become the preferred scheme for reducing energy consumption of the data center.

In a data center, in order to reduce energy consumption, some power consumption control methods, such as DVFS, etc., are preset, and when conditions corresponding to the power consumption control methods are triggered, the power consumption control methods are started to reduce energy consumption of equipment. However, the existing power consumption control scheme has poor energy saving effect.

Disclosure of Invention

Various aspects of the present application provide a power consumption control and scheme generation method, device, system, and storage medium, so as to implement dynamic power consumption control and improve an energy saving effect of power consumption control.

The embodiment of the application provides a method for generating a power consumption control scheme, which comprises the following steps: acquiring relevant parameters of target equipment, wherein the relevant parameters comprise power consumption index data of the target equipment in a historical period; predicting power consumption index data of the target device in a future period according to the power consumption index data of the target device in a historical period; and generating a power consumption control scheme used by the target device in a future period according to the power consumption index data of the target device in the future period.

An embodiment of the present application further provides a method for generating a power consumption control scheme, including: acquiring related parameters of an equipment group, wherein the related parameters comprise power consumption index data of the equipment group in a historical period, and the equipment group comprises at least one piece of physical equipment; predicting power consumption index data of the equipment group in a future time period according to the power consumption index data of the equipment group in a historical time period; and generating a power consumption control scheme used by the equipment group in the future time period according to the power consumption index data of the equipment group in the future time period.

An embodiment of the present application further provides a power consumption control method, including: receiving a newly arrived first power consumption control scheme; replacing a currently used second power consumption control scheme with the first power consumption control scheme; and controlling the power consumption of the equipment according to the first power consumption control scheme.

An embodiment of the present application further provides a power consumption control method, including: receiving a newly arrived first power consumption control scheme; obtaining a third power consumption control scheme according to the first power consumption control scheme and the currently used second power consumption control scheme; and replacing the currently used second power consumption control scheme with the third power consumption control scheme, and controlling the power consumption of the equipment according to the third power consumption control scheme.

The embodiment of the present application further provides a power consumption prediction method, including: acquiring relevant parameters of target equipment, wherein the relevant parameters comprise power consumption index data of the target equipment in a historical period; and predicting the power consumption index data of the target device in a future period according to the power consumption index data of the target device in the historical period.

An embodiment of the present application further provides a computing device, including: a memory and a processor; the memory for storing a computer program; the processor, coupled with the memory, to execute the computer program to: acquiring relevant parameters of target equipment, wherein the relevant parameters comprise power consumption index data of the target equipment in a historical period; predicting power consumption index data of the target device in a future period according to the power consumption index data of the target device in a historical period; and generating a power consumption control scheme used by the target device in the future time period according to the power consumption index data of the target device in the future time period.

An embodiment of the present application further provides a computing device, including: a memory and a processor; the memory for storing a computer program; the processor, coupled with the memory, to execute the computer program to: acquiring related parameters of an equipment group, wherein the related parameters comprise power consumption index data of the equipment group in a historical period, and the equipment group comprises at least one piece of physical equipment; predicting power consumption index data of the equipment group in a future time period according to the power consumption index data of the equipment group in a historical time period; and generating a power consumption control scheme used by the equipment group in the future time period according to the power consumption index data of the equipment group in the future time period.

An embodiment of the present application further provides a physical device, including: a memory, a processor, and a communication component; the communication component to receive a newly arrived first power consumption control scheme; the memory for storing a computer program, the first power consumption control scheme, and a currently used second power consumption control scheme; the processor, coupled with the memory, to execute the computer program to: replacing a currently used second power consumption control scheme with the first power consumption control scheme; and controlling the power consumption of the physical equipment according to the first power consumption control scheme.

An embodiment of the present application further provides a physical device, including: a memory, a processor, and a communication component; the communication component to receive a newly arrived first power consumption control scheme; the memory for storing a computer program, the first power consumption control scheme, and a currently used second power consumption control scheme; the processor, coupled with the memory, to execute the computer program to: obtaining a third power consumption control scheme according to the first power consumption control scheme and the currently used second power consumption control scheme; and replacing the currently used second power consumption control scheme with the third power consumption control scheme, and performing power consumption control on the physical equipment according to the third power consumption control scheme.

An embodiment of the present application further provides a computing device, including: a memory and a processor; the memory for storing a computer program; the processor, coupled with the memory, to execute the computer program to: acquiring relevant parameters of target equipment, wherein the relevant parameters comprise power consumption index data of the target equipment in a historical period; and predicting the power consumption index data of the target device in a future period according to the power consumption index data of the target device in the historical period.

An embodiment of the present application further provides a data center system, including: at least one machine room and power consumption control equipment; each machine room comprises at least one physical device; the power consumption control device is used for acquiring relevant parameters of a target device, wherein the relevant parameters comprise power consumption index data of the target device in a historical period; predicting power consumption index data of the target device in a future period according to the power consumption index data of the target device in a historical period; generating a power consumption control scheme used by the target device in a future period according to the power consumption index data of the target device in the future period, and providing the power consumption control scheme to the target device so as to control the power consumption of the target device in the future period; wherein the target device is any one of the at least one physical device.

The embodiment of the present application further provides a machine room system, including: the computer room comprises at least one physical device and power consumption control devices; the power consumption control device is used for acquiring relevant parameters of a target device, wherein the relevant parameters comprise power consumption index data of the target device in a historical period; predicting power consumption index data of the target device in a future period according to the power consumption index data of the target device in a historical period; generating a power consumption control scheme used by the target device in a future period according to the power consumption index data of the target device in the future period, and providing the power consumption control scheme to the target device so as to control the power consumption of the target device in the future period; wherein the target device is any one of the at least one physical device.

Embodiments of the present application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to implement the steps in the method embodiments of the present application.

In the embodiment of the application, power control is abstracted into a scheme, the power control scheme of each physical device or device group is dynamically updated through artificial intelligence, dynamic power consumption control is realized, power consumption control can be accurately controlled to each physical device or device group, different physical devices or device groups can carry out power consumption control schemes adaptive to power consumption conditions of the different physical devices or device groups, power consumption control accuracy can be improved, and the overall energy-saving effect of power consumption control can be improved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

FIG. 1a is a schematic block diagram of a machine room system provided in an exemplary embodiment of the present application;

FIG. 1b is a functional block diagram of a power consumption control device according to an exemplary embodiment of the present disclosure;

fig. 1c is a schematic diagram of an internal structure of a power consumption control device according to an exemplary embodiment of the present application;

fig. 2 is a schematic structural diagram of a data center system according to an exemplary embodiment of the present application;

fig. 3a is a schematic flowchart of a power consumption control method according to an exemplary embodiment of the present disclosure;

FIG. 3b is a schematic flow chart illustrating another power consumption control method according to an exemplary embodiment of the present disclosure;

fig. 4a is a schematic flowchart of a power consumption control scheme generation method according to an exemplary embodiment of the present application;

fig. 4b is a schematic flowchart of another power consumption control scheme generation method according to an exemplary embodiment of the present application;

fig. 4c is a schematic flowchart of another power consumption control scheme generation method according to an exemplary embodiment of the present application;

fig. 4d is a schematic flowchart of a power consumption prediction method according to an exemplary embodiment of the present disclosure.

FIG. 5a is a schematic structural diagram of a computing device according to an exemplary embodiment of the present application;

FIG. 5b is a schematic block diagram of another computing device provided in an exemplary embodiment of the present application;

FIG. 6a is a schematic structural diagram of a physical device according to an exemplary embodiment of the present application;

FIG. 6b is a schematic diagram of another physical device according to an exemplary embodiment of the present application;

fig. 7 is a schematic structural diagram of another computing device according to an exemplary embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only a few embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

Aiming at the technical problem that the existing power consumption control scheme is poor in energy saving effect, in some embodiments of the application, power control is abstracted into the scheme, the power control scheme of each physical device or device group is dynamically updated through artificial intelligence, dynamic power consumption control is achieved, power consumption control can be accurate to each physical device or device group, different physical devices or device groups can carry out power consumption control schemes matched with power consumption conditions of the different physical devices or device groups, the accuracy of power consumption control can be improved, and the overall energy saving effect of the power consumption control can be improved.

The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.

Fig. 1a is a schematic structural diagram of a machine room system according to an exemplary embodiment of the present disclosure. As shown in fig. 1a, the machine room system 100 of the present embodiment includes: the machine room refers to a physical place for storing the machine equipment, and may be, for example, a room or a factory building. Further, as shown in fig. 1a, the machine room system 100 further includes: at least one physical device 101 and a power consumption control device 102 located in a computer room. In this embodiment, the number of the physical devices 101 in the computer room is not limited, and may be one or multiple.

In the present embodiment, the device form of the physical device 101 is not limited. As shown in fig. 1a, the physical device 101 may be an IT-type device in a machine room and a cooling device for cooling the IT-type device, such as an air conditioner. By way of example, the at least one physical device 101 may include, but is not limited to: cabinet equipment, server equipment, computer equipment, printers, hubs, power supply equipment, storage equipment, network switching equipment, air conditioning equipment, and the like. The server device may be, including but not limited to: a conventional server, a server array, or a cloud server, etc. The power supply device may be a battery device, a dry battery device, or an Uninterruptible Power Supply (UPS) or the like. Storage devices may include, but are not limited to: disks, disk arrays, hard disks, network storage devices (NAS), and the like.

In order to reduce the energy consumption of the computer room system 100, it is necessary to perform power consumption control on at least one physical device 101. In this embodiment, a power consumption control scheme may be configured for the physical device 101, and the physical device 101 performs power consumption control according to the power consumption control scheme. The power consumption control scheme is a scheme for instructing the physical device 101 to perform power consumption control, and includes a trigger condition and a power consumption control method. When the trigger condition in the power consumption control scheme is satisfied, the power consumption control method in the power consumption control scheme is executed. Here, the power control method may be understood as a power control action, and when the trigger condition is satisfied, the power control action corresponding to the trigger condition is executed.

In this embodiment, the power consumption control method is not limited, and any method having the functions of controlling, limiting or adjusting the power consumption is suitable for the embodiment of the present application. For example, power control methods include, but are not limited to: power Capping (Power Capping), dynamic Voltage and Power Scaling (DVFS), C-mode (C-State), and the like. Among other things, power capping is a method of limiting the power consumption of a device that can ensure that the actual power consumption of the device is below the maximum power available and that the device uses lower power consumption when the device load is low. DVFS is a dynamic technique for dynamically adjusting the operating frequency and voltage of a chip (e.g., CPU) according to the different requirements of the application running on the chip for computing power, thereby achieving the goal of saving energy, and can adjust the power and voltage of various processors, control chips, and peripheral devices on the device. C-state is a low power consumption mechanism which can enable the CPU to enter a low power consumption state when in an idle state, C modes contained in the C-state are started from C0 to Cn, the C0 is a normal working mode of the CPU, and the CPU is in a 100% running state; the higher the value of n behind C is, the deeper the CPU sleeps, the smaller the power consumption of the CPU is, and certainly, the more time is needed for returning to the C0 mode; wherein n is a positive integer.

In an extreme case, if the power consumption of at least one physical device 101 in the computer room is the same or substantially the same at any time, the power consumption control scheme may be configured for at least one physical device 101 in a unified manner, and all the physical devices 101 use the same power consumption control scheme to perform power consumption control.

However, in most cases, the load conditions of different physical devices 101 in the machine room are greatly different, and the loads of different physical devices 101 are different even at the same time, so that the power consumption conditions of different physical devices 101 are different. For such a situation, if a power consumption control scheme is still uniformly configured for at least one physical device 101, and the physical devices 101 with different power consumption perform power consumption control according to the same power consumption control scheme, obviously, the overall energy saving effect is not ideal. In addition, even if the same physical device 101 is loaded differently at different times, this means that the power consumption of the same physical device 101 is different at different times.

Based on the above analysis, in this embodiment, artificial intelligence is introduced, and the power consumption control scheme of each physical device 101 is dynamically updated through the artificial intelligence, so as to implement dynamic power consumption control and improve the energy saving effect of the power consumption control. In order to dynamically update the power consumption control scheme of each physical device 101, a power consumption control device 102 is additionally provided in the computer room. The power consumption control device 102 dynamically updates the power consumption control scheme of each physical device 101 mainly based on artificial intelligence, so that each physical device 101 performs power consumption control according to the dynamically changed power consumption control scheme.

The manner in which the power consumption control device 102 dynamically updates the power consumption control scheme for each physical device 101 is the same or similar. In this embodiment, a process of dynamically updating a power consumption control scheme for a physical device 101 by a power consumption control device 102 is described with reference to a schematic block diagram shown in fig. 1b and taking one of the physical devices 101 as an example. For convenience of description, in the following description, the physical device is referred to as a target device, and the target device is any one of the at least one physical device 101.

The power consumption control device 102 may obtain relevant parameters of the target device, where the relevant parameters include: power consumption index data of the target device in a historical period; predicting the power consumption index number of the target equipment in a future period according to the power consumption index data of the target equipment in a historical period; and further, according to the power consumption index data of the target device in the future time period, generating a power consumption control scheme used by the target device in the future time period, and providing the power consumption control scheme for the target device to perform power consumption control in the future time period according to the power consumption control scheme.

In the present embodiment, the time length of the future period is not limited. For example, the future time period may be the next half hour (upcoming half hour), or the next hour (upcoming hour), or the next hours (upcoming hours), or the future day (upcoming day), or the future week (upcoming week), or a certain time period within the next hour, or a certain time period within the future day, or a certain day or days within the future week, etc. The time length of the future time period can be flexibly set according to application requirements. In addition, the time lengths of the future periods may be the same or different for different physical devices 101.

For each future time period, the power consumption control device 102 predicts the power consumption index data of the target device in the future time period according to the power consumption index data of the target device in the corresponding historical time period, and generates a power consumption control scheme used by the target device in the future time period according to the power consumption index data of the target device in the future time period. That is, the power consumption control device 102 dynamically updates the power consumption control scheme used by the target device in each future period according to changes in the future period; in the long term, the power consumption control scheme used by the target device is dynamically changed, and dynamic power consumption control can be realized.

In the present embodiment, the history period refers to a period of time before the current time, and belongs to the history period with respect to the current time, for example, yesterday morning, yesterday afternoon, last tuesday, last monday to wednesday, last saturday, last sunday, and the like. In this embodiment, the number of used history periods is not limited, and the history period may be one or more; in addition, the time length of each historical time interval is not limited, and the time length can be adaptively set according to application requirements. Similarly, the embodiment does not limit the corresponding relationship between the historical time period and the future time period, and can be adaptively set according to application requirements. The following examples illustrate:

for example, the power consumption index data of the target device on the weekend of the week may be predicted from the power consumption index data of the target device on each weekend in the last three months, and the power consumption control plan for use of the target device on the weekend of the week may be generated from the power consumption index data of the target device on the weekend of the week.

For example, the power consumption index data of the target device in the future week can be predicted according to the power consumption index data of the target device in the last month, and then the power consumption control scheme used by the target device in the future week can be generated according to the power consumption index data of the target device in the future week.

For example, power consumption index data of the target device between 10 am and 12 am of each day of the future week may be predicted from the power consumption index data of the target device between 10 am and 12 am of each day of the last week; and generating a power consumption control scheme used by the target device in the future week according to the power consumption index data of the target device between 10 and 12 am every day in the future week.

For example, the power consumption index data of the target device in the day and the power consumption index data of the target device in the evening in the future day can be predicted according to the power consumption index data of the target device in the day and the power consumption index data of the target device in the evening in the last days; and generating a power consumption control scheme used by the target equipment in the future day according to the power consumption index data of the target equipment in the day and the power consumption index data of the target equipment in the evening.

In this embodiment, the power consumption index data refers to some data related to power consumption, and may include one kind of data or multiple kinds of data. Wherein a kind of the power consumption index data used in the future period is the same as a kind of the power consumption index data used in the history period; alternatively, the kind of power consumption index data used in the future period is a part of the kind of power consumption index data used in the history period. The power consumption indicator data associated with a device may also vary for different types of devices.

For example, in the case of the IT-type device, the internal temperature, power consumption, CPU frequency, CPU load, and the like of the IT-type device are all related to the power consumption of the IT-type device, and therefore, at least one of the internal temperature, power consumption, CPU frequency, CPU load, and the like of the IT-type device may be used as the power consumption index data.

In an optional embodiment, taking the power consumption and the CPU frequency of the IT-class device as power consumption index data as an example, when the target device is the IT-class device, the power consumption control device 102 may obtain the power consumption and the CPU frequency of the target device in a historical period as the power consumption index data of the target device in the historical period; predicting the power consumption and the CPU frequency of the target device in a future period according to the power consumption and the CPU frequency of the target device in a historical period; and generating a power consumption control scheme used by the target device in the future period according to the power consumption of the target device in the future period and the CPU frequency.

In another optional embodiment, taking the selection of the power consumption, the CPU frequency, and the CPU load of the IT-class device as the power consumption index data as an example, in the case that the target device is the IT-class device, the power consumption control device 102 may obtain the power consumption, the CPU frequency, and the CPU load of the target device in the historical period as the power consumption index data of the target device in the historical period; predicting the power consumption, the CPU frequency and the CPU load of the target device in a future period according to the power consumption, the CPU frequency and the CPU load of the target device in a historical period; and generating a power consumption control scheme used by the target device in the future period according to the power consumption, the CPU frequency and the CPU load of the target device in the future period.

In yet another optional embodiment, taking the internal temperature, power consumption, CPU frequency and CPU load of the IT-class device as the example of selecting the power consumption index data, in the case that the target device is the IT-class device, the power consumption control device 102 may obtain the internal temperature, power consumption, CPU frequency and CPU load of the target device in the historical period as the power consumption index data of the target device in the historical period; predicting the power consumption and the CPU load of the target device in a future period according to the internal temperature, the power consumption, the CPU frequency and the CPU load of the target device in a historical period; and generating a power consumption control scheme used by the target device in the future period according to the power consumption of the target device in the future period and the CPU load.

For example, in the case of an air conditioner, data such as the frequency of a compressor of the air conditioner, the rotational speed of a fan, the return air temperature, and the outlet air temperature are related to the power consumption of the air conditioner, and therefore, at least one of the frequency of the compressor of the air conditioner, the rotational speed of the fan, the return air temperature, and the outlet air temperature may be used as power consumption index data.

In an optional embodiment, taking the selection of the frequency of the compressor and the rotation speed of the fan of the air conditioning equipment as power consumption index data as an example, if the target equipment is the air conditioning equipment, the power consumption control equipment 102 may obtain the frequency of the compressor and the rotation speed of the fan of the target equipment in a historical period as power consumption index data of the target equipment in the historical period; predicting the frequency of the compressor and the rotating speed of the fan of the target equipment in a future period according to the frequency of the compressor and the rotating speed of the fan of the target equipment in a historical period; and generating a power consumption control scheme used by the target equipment in the future period according to the frequency of the compressor and the rotating speed of the fan of the target equipment in the future period.

In another optional embodiment, taking the frequency of the compressor of the air conditioning equipment, the rotating speed of the fan, the return air temperature, and the outlet air temperature as power consumption index data as an example, when the target equipment is the air conditioning equipment, the power consumption control equipment 102 may obtain the frequency of the compressor, the rotating speed of the fan, the return air temperature, and the outlet air temperature of the target equipment in a historical period as power consumption index data of the target equipment in the historical period; predicting the frequency of a compressor, the rotating speed of a fan, the return air temperature and the outlet air temperature of target equipment in a future period according to the frequency of the compressor, the rotating speed of the fan, the return air temperature and the outlet air temperature of the target equipment in a historical period; and generating a power consumption control scheme used by the target equipment in the future period according to the frequency of the compressor, the rotating speed of the fan, the return air temperature and the outlet air temperature of the target equipment in the future period.

In yet another optional embodiment, taking the frequency of the compressor of the air conditioning equipment, the rotation speed of the fan, the return air temperature, and the outlet air temperature as power consumption index data as an example, when the target equipment is the air conditioning equipment, the power consumption control equipment 102 may obtain the frequency of the compressor, the rotation speed of the fan, the return air temperature, and the outlet air temperature of the target equipment in a historical period as power consumption index data of the target equipment in the historical period; predicting the return air temperature and the outlet air temperature of the target equipment in a future time period according to the frequency of a compressor, the rotating speed of a fan, the return air temperature and the outlet air temperature of the target equipment in a historical time period; and generating a power consumption control scheme used by the target equipment in the future time period according to the return air temperature and the outlet air temperature of the target equipment in the future time period.

Further alternatively, for IT-class devices, there are cases where the power consumption is affected by other devices associated with the IT-class devices, for example, for servers located in a rack, a portion of the power consumption of the rack is transmitted to the servers. Based on this, when the target device is an IT-type device, in addition to acquiring various power consumption index data of the target device itself related to power consumption, other devices related to the target device may be determined according to a topology structure between the target device and the other devices, and power consumption of the other devices related to the target device in a historical period is acquired and also taken as one type of power consumption index data of the target device in the historical period. Wherein the other device associated with the target device refers to a device having an influence on power consumption of the target device.

In the present embodiment, the manner in which the power consumption control device 102 acquires the power consumption index data of the target device in the history period is not limited. In some optional embodiments, the power consumption control device 102 may provide a human-machine interaction interface through which a manager of the computer room may input power consumption index data of the target device in a historical period to the power consumption control device 102. The man-machine interaction interface can be realized in various modes. For example, the human-computer interaction interface may be implemented as a web page or an application page containing an input box in which a manager may input power consumption index data of the target device during a historical period. Or, the human-computer interaction interface may be implemented as a web page or an application page including a power consumption index data option drop-down box, and the manager may select power consumption index data to be input from the drop-down box through the power consumption index data option drop-down box. In other alternative embodiments, the power consumption control device 102 supports a configuration file, and then the administrator may send the configuration file to the power consumption control device 102 through another device (for example, a terminal device used by the administrator), where the configuration file includes power consumption index data of the target device in a historical period; the power consumption control device 102 may read power consumption index data of the target device over a historical period from the configuration file.

For the target device, the power consumption control scheme provided by the power consumption control device 102 may be acquired, and power consumption control may be performed according to the power consumption control scheme. The process of the target device for controlling the power consumption according to the power consumption control scheme comprises the following steps: monitoring whether a trigger condition in a power consumption control scheme is met; and under the condition that the triggering condition is met, performing power consumption control according to a power consumption control method in the power consumption control scheme.

Wherein the trigger condition in the power consumption control scheme is a condition required to trigger the target device to initiate power consumption control. For example, the trigger condition may be a time range indicating that the corresponding power consumption control method needs to be started for power consumption control in the time range. Or, the trigger condition is a power consumption index data range, which indicates that when the power consumption index data is in the range, a corresponding power consumption control method needs to be started for power consumption control. The power consumption index data range as the trigger condition is different according to different power consumption index data.

For example, assuming that the power consumption indicator data includes power consumption, the power consumption indicator data range correspondingly includes: range of power consumption. When the actual power consumption of the target device in a short period of time is within the power consumption range, the corresponding power consumption control method can be started to perform power consumption control. Further alternatively, the power consumption control may be ended if the actual power consumption of the target device for a short period of time is lower than the lower limit value of the power consumption range.

For example, assuming that the power consumption index data includes power consumption and CPU frequency, the power consumption index data range includes: power consumption range and CPU frequency range. In one implementation, when both trigger conditions are satisfied, for example, when the actual power consumption of the target device in a short period of time is within the power consumption range and the actual CPU frequency of the target device in a short period of time is within the CPU range, the corresponding power consumption control method is started for power consumption control. Accordingly, when either of the two trigger conditions is no longer satisfied, the power consumption control may be ended. In another implementation, when any one of the conditions is satisfied, that is, when the actual power consumption of the target device in a short period of time is within the power consumption range, or when the actual CPU frequency of the target device in a short period of time is within the CPU frequency range, the corresponding power consumption control method is started to perform power consumption control. Accordingly, when neither of the two trigger conditions is satisfied, the power consumption control may be ended.

In the above embodiment, the actual power consumption or the actual CPU frequency in a short period of time is selected to maintain the stability of power consumption control and minimize the probability of the ping-pong effect. The time length of the "short time" is not limited, and may be 10 seconds, 1 minute, 5 minutes, or the like. Of course, in addition to the power consumption control based on the actual power consumption or the actual CPU frequency in a short period of time, the power consumption control based on the real-time power consumption or the power consumption index data such as the CPU frequency may also be used.

In this embodiment, power control is abstracted as a scheme, the power control scheme of each physical device is dynamically updated through artificial intelligence, dynamic power consumption control is realized, power consumption control can be accurate to each physical device, different physical devices can perform power consumption control schemes adaptive to power consumption conditions of the physical devices, power consumption control accuracy can be improved, and the overall energy-saving effect of power consumption control can be improved.

In some embodiments of the present application, after obtaining the power consumption index data of the target device in the historical period, the power consumption control device 102 may predict the power consumption index data of the target device in a future period directly according to the power consumption index data of the target device in the historical period.

In other embodiments of the present application, in order to improve the accuracy of the prediction result, the target devices may be classified; if the target equipment belongs to equipment of which the power consumption change meets the rule requirement, then the operation of predicting the power consumption index data of the target equipment in the future time period according to the power consumption index data of the target equipment in the historical time period is executed; if the target device does not belong to a device whose power consumption change meets the rule requirement, the operation of generating the power consumption control scheme for the target device is finished, or a default power consumption control scheme, such as DVFS, is set for the target device.

Optionally, in order to classify the target device more accurately, device parameters of the target device may be added. The device parameters mainly refer to static parameters related to the device itself, such as device type, device model, device serial number, device specification, and so on. The device parameters of the target device may be acquired from the target device or may be acquired in an out-of-band manner. Based on this, as shown in fig. 1b, the power consumption control device 102 needs to obtain the device parameters of the target device in addition to the power consumption index data of the target device in the historical time period, and identifies whether the target device belongs to a device whose power consumption changes meet the rule requirement according to the device parameters of the target device and the power consumption index data of the target device in the historical time period. As for the manner in which the power consumption control device 102 obtains the device parameter of the target device, reference may be made to the manner in which the power consumption control device 102 obtains the power consumption index data of the target device in the historical time period, which is not described herein again.

Further, as shown in fig. 1c, one internal structure of the power consumption control device 102 includes: a classifier, a predictor and a decider. The classifier is mainly responsible for classifying the target equipment according to equipment parameters of the target equipment and power consumption index data of the target equipment in a historical time period so as to identify whether the target equipment belongs to equipment with power consumption change meeting the rule requirement and output a classification result; if the target equipment belongs to equipment of which the power consumption change meets the rule requirement, entering a predictor; and if the target equipment does not belong to the equipment with the power consumption change meeting the rule requirement, entering a decision maker. The predictor is mainly used for predicting the power consumption index data of the target device in the future period according to the power consumption index data of the target device in the historical period and outputting the power consumption index data to the decision maker. The decision maker is used for generating a power consumption control scheme used by the target equipment in a future period according to power consumption index data of the target equipment in the future period under the condition that the target equipment belongs to equipment of which the power consumption change meets the rule requirement; or, in the case that the target device does not belong to a device whose power consumption change meets the rule requirement, a default power consumption control scheme may be set for the target device.

In an alternative embodiment, the target device may be classified using a classification model. The device parameters of the target device and the power consumption index data of the target device in the historical period can be input into the classification model to obtain whether the target device belongs to the classification result of the device with the power consumption change meeting the rule requirement.

In the classification model, a reference distribution characteristic corresponding to the type of equipment to which the target equipment belongs can be determined according to the equipment parameters of the target equipment, and the reference distribution characteristic is a distribution characteristic of power consumption index data meeting the rule requirement; and classifying the target equipment according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target equipment in the historical time period to obtain whether the target equipment belongs to the classification result of the equipment with the power consumption change meeting the rule requirement.

Optionally, the similarity between the reference distribution feature and the distribution feature of the power consumption index data of the target device in the historical period may be directly calculated, and the target device may be classified according to the similarity; if the similarity is larger than a set similarity threshold, determining that the target equipment belongs to equipment of which the power consumption change meets the rule requirement; and if the similarity is less than or equal to the set similarity threshold, determining that the target equipment does not belong to the equipment of which the power consumption change meets the rule requirement.

Optionally, the target device may be classified by using a logistic regression algorithm or a random forest algorithm according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target device in the historical time period, so as to obtain a classification result of whether the target device belongs to a device whose power consumption change meets the rule requirement.

For example, by classifying the target device by using a logistic regression algorithm, it is possible to use whether the target device belongs to a device whose power consumption change meets the rule requirement as a binary problem, the output is y ∈ {0,1}, a linear regression model z = wTx + b is a real value, and the value of z is converted to 0 or 1 by a Sigmoid function. For example, if the value calculated by the Sigmoid function is greater than or equal to 0.5, it is classified as category 1; if the value calculated by the Sigmoid function is less than 0.5, the result is classified as class 0. In this embodiment, category 1 indicates that the target device belongs to a device whose power consumption changes satisfy the rule requirement; class 0 indicates that the target device does not belong to a device whose power consumption changes meet the regulatory requirements.

In the logistic regression process, a cost function can be defined, the reference distribution characteristics are used as a training set, and the defined cost function is used as a target to train (fit) to obtain a value of wT; then, taking the distribution characteristics of the power consumption index data of the target equipment in the historical time period as the value of x, and substituting the value of z into a two-linear regression model z = wTx + b to obtain the value of z; and converting the value of z into 0 or 1 through a Sigmoid function to obtain a classification result of whether the target equipment belongs to equipment of which the power consumption change meets the rule requirement. Where b is a constant generally conforming to a normal distribution with a mean value of 0.

Taking the classification of the target device by adopting a random forest algorithm as an example, the reference distribution characteristics can be used as training samples to construct a plurality of decision trees, then the distribution characteristics of the power consumption index data of the target device in a historical time period are classified by using the plurality of decision trees, and finally whether the target device belongs to a device with power consumption change meeting the rule requirement is determined according to voting of the plurality of decision trees. The process of constructing multiple decision trees can be referred to in the prior art, and is not described in detail herein.

In the above-described embodiment or the following-described embodiment of the present application, the power consumption index data of the target device in the future period may be predicted by using a machine learning model in artificial intelligence, for example, a prediction model. Wherein, the power consumption index data of the target device in the historical period can be input into the prediction model to obtain the power consumption index data of the target device in the future period.

In the prediction model, according to the power consumption index data of the target device in the historical time period, a linear regression algorithm or a deep learning algorithm is adopted to predict the power consumption index data of the target device in the future time period. The training process and the prediction process of the prediction model using the linear regression algorithm or the deep learning algorithm are the same as or similar to those of the prior art, and are not described herein again.

In some embodiments of the present application, in predicting the power consumption index data of the target device in the future period, in addition to considering the power consumption index data of the target device in the historical period, the performance index data of the target device in the historical period may be combined, as shown in fig. 1 b. The performance index data herein refers to data that can reflect the service performance of the target device. In the case that the target device is an IT-type device, at least one application or service may be run on the target device, such as a cloud computing service, a game service, an instant messaging service, a mail service, or an online transaction service. The performance indicator data of the target device may be QoS data of an application or service running on the target device. For example, for an application or service, the QoS data may be response time, TPS, QPS, or the number of concurrent users, etc.

In an optional embodiment, during the operation of the target device, performance index data of the target device may be collected and stored in the database. Based on this, performance index data of the target device over the historical period may be obtained from the database.

In another alternative embodiment, the Service provider may provide the target device to a certain user, and in order to guarantee the performance and availability of the Service, the Service provider and the user may define a two-party agreed Agreement, namely Service Level Agreement (SLA), in which the performance requirements that the target device needs to meet are agreed. Based on this, the performance index data that the target device needs to meet can be obtained from the SLA agreement corresponding to the target device, and the performance index data is taken as the performance index data of the target device in the historical period.

In combination with the performance index data of the target device in the historical period, the power consumption index data of the target device in the historical period and the performance index data of the target device in the historical period may be input into the prediction model to obtain the power consumption index data of the target device in the future period. In this embodiment, the influence of the performance index data on the power consumption index data is considered, which is beneficial to improving the accuracy of the prediction result, and further a more reasonable power consumption control scheme can be generated for the target device, so that the accuracy of power consumption control is improved.

In the above or below embodiments of the present application, after the power consumption index data of the target device in the future period is obtained, a power consumption control scheme used by the target device in the future period may be generated according to the power consumption index data of the target device in the future period.

In some embodiments of the present application, the power consumption control scheme may be generated based on a rule, that is, some trigger conditions and power consumption control methods corresponding to the trigger conditions are predefined. Based on this, the process of generating the power consumption control scheme used by the target device for the future period of time includes: matching the power consumption index data of the target equipment in a future time period with preset trigger conditions, and determining the matched target trigger conditions in the preset trigger conditions; acquiring a preset power consumption control method corresponding to a target trigger condition, such as DVFS or C-State, as a target power consumption control method; and generating a power consumption control scheme used by the target device in a future time period according to the target trigger condition and the target power consumption control method. In this embodiment, the power consumption control scheme used by the target device for the future period includes: a target trigger condition and a target power consumption control method.

In other embodiments of the present application, the power consumption control scheme may be generated by combining a rule and artificial intelligence, that is, some trigger conditions may be predefined, and in the case that the trigger conditions are matched, a power consumption control method adapted to the trigger conditions may be generated by using artificial intelligence. Based on this, the process of generating the power consumption control scheme used by the target device for the future period includes: matching with preset trigger conditions according to power consumption index data of the target equipment in a future time period, and determining matched target trigger conditions in the preset trigger conditions; simulating the energy-saving effect of various power consumption control methods under the target triggering condition; selecting a power consumption control method with the energy-saving effect meeting the energy-saving requirement from the energy-saving effects of various power consumption control methods under the target trigger condition as a target power consumption control method; and generating a power consumption control scheme used by the target device in a future time period according to the target trigger condition and the target power consumption control method. In this embodiment, the power consumption control scheme used by the target device for the future period includes: target trigger conditions and target power consumption control methods, such as 6 a.m.: 00-8:00, DVFS is executed.

Further, in either the embodiment that the power consumption control scheme is generated based on the rule or the embodiment that the power consumption control scheme is generated by combining the rule and the artificial intelligence, in addition to the predefined trigger condition, a performance index data range corresponding to the trigger condition may be predefined, where the performance index data range may be understood as a constraint condition for power consumption control and is a performance requirement that needs to be ensured in the power consumption control process. It is worth noting that not every trigger condition corresponds to a range of performance indicator data. Based on the method, after the target triggering condition is determined, whether the target triggering condition has a corresponding performance index data range can be judged; if yes, acquiring a preset performance index data range corresponding to the target trigger condition as a target performance index data range; and then, generating a power consumption control scheme used by the target equipment in a future time period according to the target trigger condition, the target power consumption control method and the target performance index data range. In this embodiment, the power consumption control scheme used by the target device in the future period includes: target trigger conditions, target power consumption control methods, and target performance index data ranges.

Further, in either the embodiment of generating the power consumption control scheme based on the rule or the embodiment of generating the power consumption control scheme by combining the rule and the artificial intelligence, the preset trigger condition may include at least one of the following: a trigger condition representing a time range and a trigger condition representing a power consumption indicator data range. Here, the trigger condition indicating the time range means: and starting a corresponding power consumption control method to control the power consumption within the time range represented by the trigger condition. The trigger condition for representing the time range may be plural depending on the time range represented. The trigger condition indicating the power consumption index data range means: and when the actual power consumption index data of the target equipment in a short period of time is in the power consumption index data range represented by the trigger condition, starting a corresponding power consumption control method to control the power consumption. Similarly, there may be a plurality of trigger conditions representing the range of the power consumption index data according to different power consumption index data.

Based on the above, matching the power consumption index data of the target device in the future time period with the preset trigger condition, and determining the matched target trigger condition in the preset trigger condition may include at least one of the following manners:

mode 1: according to the time range corresponding to the future time period, the trigger condition of which the represented time range falls within the time range corresponding to the future time period is determined as the target trigger condition from the trigger conditions which are preset to represent the time range. For example, assume that a future period refers to the morning of the future day, and that a certain trigger condition indicates a time range of 6 a.m.: 00-8:00, another trigger condition represents a time range of 2 pm: 00-4:00, then 6 am: 00-8: the trigger condition of 00 is a target trigger condition.

Mode 2: according to the power consumption index data of the target device in the future time period, from the preset trigger conditions representing the power consumption index data range, determining the trigger conditions, which have appeared in the power consumption index data of the target device in the future time period, of the represented power consumption index data range as target trigger conditions. For example, assuming that the power consumption index data of the target device in the future period includes power consumption, and the power consumption value fluctuates between 10w and 30w, a certain trigger condition indicates a power consumption range greater than 20w, and another trigger condition indicates a power consumption range greater than 50w, the trigger condition greater than 20w is the target trigger condition.

In the embodiments of the present application, after obtaining the power consumption control scheme used by the target device in the future period, the power consumption control device 102 provides the target device with the power consumption control scheme used by the target device in the future period. For the target device, after receiving a new power consumption control scheme provided by the power consumption control device 102 each time, power consumption control may be performed according to the new power consumption control scheme.

In some embodiments of the present application, a target device receives a newly arrived power consumption control scheme; and replacing the currently used power consumption control scheme with the newly arrived power consumption control scheme, so as to control the power consumption according to the newly arrived power consumption control scheme. For convenience of description and distinction, a newly arrived power consumption control scheme is referred to as a first power consumption control scheme, and a currently used power consumption control scheme is referred to as a second power consumption control scheme. In this embodiment, whenever a new power consumption control scheme arrives, the old power consumption control scheme is overwritten by the new power consumption control scheme, which is simple and easy to implement.

Wherein the first power consumption control scheme comprises: trigger conditions and power consumption control methods. Based on this, the process of the target device performing power consumption control according to the first power consumption control scheme is as follows: monitoring whether a trigger condition in a first power consumption control scheme is met; and under the condition that the trigger condition in the first power consumption control scheme is met, performing power consumption control on the target equipment by using a power consumption control method corresponding to the met trigger condition in the first power consumption control scheme. Taking the triggering conditions as 6 a.m.: 00-8:00, taking the power consumption control method DVFS as an example, in 6 a.m.: 00-8: during the period of 00, DVFS can be started for power consumption control.

Further optionally, in the process of performing power consumption control on the target device according to the first power consumption control scheme, actual performance index data, such as actual QoS data, of the target device is monitored; and the control strength of the first power consumption control scheme may be adjusted according to actual performance index data of the target device.

For example, actual performance data of the target device may be compared to a specified performance lower limit; and if the actual performance data of the target equipment is smaller than the designated performance lower limit value, shutting down the first power consumption control scheme until the actual performance index data of the target equipment is larger than or equal to the designated performance lower limit value.

For another example, the actual performance data of the target device may be compared to a specified performance lower limit; and if the actual performance data of the target equipment is smaller than the designated performance lower limit value, adjusting the power consumption control method in the first power consumption control scheme to be the power consumption control method with lower control intensity until the actual performance index data of the target equipment is larger than or equal to the designated performance lower limit value.

Wherein the specified lower performance limit may be a lower performance limit that is acceptable to the target device. Alternatively, in the case where the first power consumption control scenario includes a performance index data range corresponding to the trigger condition, the specified performance lower limit value may be a lower limit value of the performance index data range in the first power consumption control scenario.

In the above embodiment, the power consumption of the target device is controlled by combining the actual performance index data of the target device, which not only can save energy consumption, but also can ensure the service quality of the target device.

In still other embodiments of the present application, a target device receives a newly arrived first power consumption control scheme; obtaining a third power consumption control scheme according to the first power consumption control scheme and a currently used second power consumption control scheme; and replacing the currently used second power consumption control scheme with a third power consumption control scheme, and performing power consumption control on the equipment according to the third power consumption control scheme.

In one approach, the target device may directly merge the first power consumption control scheme and the second power consumption control scheme to obtain a third power consumption control scheme.

In another approach, the target device may compare the trigger condition in the first power consumption control scheme to the trigger condition in the second power consumption control scheme; if the triggering condition in the first power consumption control scheme is different from the triggering condition in the second power consumption control scheme in type, combining the first power consumption control scheme and the second power consumption control scheme to obtain a third control scheme; and if the triggering condition in the first power consumption control scheme is the same as the triggering condition in the second power consumption control scheme in category, the old power consumption control scheme is covered by the new power consumption control scheme, namely the first power consumption control scheme is used as a third control scheme.

For example, if the trigger condition in the first power consumption control scheme is a trigger condition indicating a time range and the trigger condition in the second power consumption control scheme is a trigger condition indicating a power consumption range, the first power consumption control scheme and the second power consumption control scheme may be combined as the third control scheme. If the trigger condition in the first power consumption control scheme is a trigger condition indicating a time range, and the trigger condition in the second power consumption control scheme is also a trigger condition indicating a time range, the second power consumption control scheme may be discarded, and the first power consumption control scheme may be retained, that is, the first power consumption control scheme may be used as the third power consumption control scheme.

The third power consumption control scheme includes a trigger condition and a power consumption control method, and there may be a combination of multiple sets of trigger conditions and power consumption control methods. Based on this, the power consumption control of the device according to the third power consumption control scheme includes: and under the condition that the trigger condition in the third power consumption control scheme is met, performing power consumption control on the target equipment by using a power consumption control method corresponding to the met trigger condition in the third power consumption control scheme.

Further optionally, in the process of performing power consumption control on the target device according to the third power consumption control scheme, actual performance index data, such as actual QoS data, of the target device is monitored; and the control strength of the third power consumption control scheme may be adjusted according to the actual performance index data of the target device.

For example, actual performance data of the target device may be compared to a specified performance lower limit; and if the actual performance data of the target equipment is smaller than the specified performance lower limit value, stopping the third power consumption control scheme until the actual performance index data of the target equipment is larger than or equal to the specified performance lower limit value.

For another example, the actual performance data of the target device may be compared to a specified performance lower limit; and if the actual performance data of the target equipment is smaller than the specified performance lower limit value, adjusting the power consumption control method in the third power consumption control scheme to be the power consumption control method with lower control intensity until the actual performance index data of the target equipment is larger than or equal to the specified performance lower limit value.

Wherein the specified lower performance limit may be a lower performance limit that is acceptable to the target device. Alternatively, in the case where the third power consumption control scheme includes the performance index data range corresponding to the trigger condition, the specified performance lower limit value may be a lower limit value of the performance index data range in the third power consumption control scheme.

Examples for the device group:

in the above-described embodiment, the power consumption control device 102 can dynamically update the power consumption control scheme of each physical device in units of one physical device, but is not limited thereto. In the embodiments described below in this application, the power consumption control device 102 may also dynamically update the power consumption control scheme of each device group in units of device groups. The device group comprises at least one physical device, and all the physical devices in the device group form a binding relationship and can share the same power consumption control scheme.

In the embodiment of the present application, the forming manner of the device group is not limited. For example, the physical devices in the room that are relatively close to each other may be divided into a device group, or the physical devices with the same or similar load conditions may be divided into a device group, or the physical devices of the same type may be divided into a device group, or the physical devices of the same model may be divided into a device group, or the physical devices of the same manufacturer may be divided into a device group, or the physical devices in the whole room may be divided into a device group, and so on.

For the power consumption control device 102, relevant parameters of a device group may be obtained, where the relevant parameters of the device group include power consumption index data of the device group in a historical period; predicting power consumption index data of the equipment group in a future time period according to the power consumption index data of the equipment group in a historical time period; and generating a power consumption control scheme used by the device group in the future period according to the power consumption index data of the device group in the future period.

In an alternative embodiment, the power consumption index data for the group of devices over the historical period includes: power consumption index data of each physical device in the device group in a historical period; accordingly, the predicted power consumption index data for the group of devices in the future time period includes: power consumption index data of each physical device in the device group in a future time period. Optionally, one prediction method is: and the individual prediction mode is that for each physical device in the device group, the power consumption index data of the physical device in the future period is individually predicted according to the power consumption index data in the historical period. Optionally, another prediction method is: and a joint prediction mode, namely performing joint prediction according to the power consumption index data of all the physical equipment in the equipment group in the historical time period to obtain the power consumption index data of each physical equipment in the future time period.

In another optional embodiment, the power consumption index data of the device group in the historical period is power consumption index data calculated according to the power consumption index data of each physical device in the device group in the historical period. The power consumption index data of the device group in the historical period can be discrete values or continuous values, and the power consumption index data of each historical moment in the historical period can be included. For example, the power consumption index data of the device group at a certain historical time may be an average value of the power consumption index data of each physical device in the device group at the same historical time, or a maximum value thereof, or a minimum value thereof, or an average value of the maximum value and the minimum value thereof, and so on. Accordingly, the power consumption index data of the device group in the future period is predicted according to the power consumption index data of the device group in the historical period, and can be a plurality of discrete values or continuous values.

In some embodiments of the present application, in order to improve the accuracy of the prediction result, the device groups may be classified; if the equipment group belongs to the equipment group with the power consumption change meeting the rule requirement, then the operation of predicting the power consumption index data of the equipment group in the future time period according to the power consumption index data of the equipment group in the historical time period is executed; if the equipment group does not belong to the equipment group with the power consumption change meeting the rule requirement, ending the operation of generating the power consumption control scheme for the equipment group, or setting a default power consumption control scheme for the equipment group.

Alternatively, in order to more accurately classify the device group, device parameters of the device group may be added. The device parameters of the device group mainly refer to some static parameters related to the physical devices themselves in the device group, such as device type, device model, device serial number, device specification, and the like. Based on this, the power consumption control device 102 needs to obtain the device parameters of the device group in addition to the power consumption index data of the device group in the historical period, and identify whether the device group belongs to the device group whose power consumption change meets the rule requirement according to the device parameters of the device group and the power consumption index data of the device group in the historical period. If the equipment group belongs to the equipment group of which the power consumption change meets the rule requirement, predicting the power consumption index data of the equipment group in the future time period according to the power consumption index data of the equipment group in the historical time period, and further generating a power consumption control scheme used by the equipment group in the future time period according to the power consumption index data of the equipment group in the future time period. If the equipment group does not belong to the equipment group with the power consumption change meeting the rule requirement, a default power consumption control scheme can be set for the equipment group.

Alternatively, a classification model may be employed in classifying the group of devices. The classification model can classify the equipment groups by adopting a logistic regression algorithm or a random forest algorithm so as to obtain whether the equipment groups belong to the classification result of the equipment groups with power consumption changes meeting the rule requirements.

Alternatively, a predictive model may be employed in predicting power consumption index data for a group of devices over a future time period. The power consumption index data for the group of devices over the historical period may be input into the predictive model to derive power consumption index data for the group of devices over a future period. The prediction model may use a linear regression algorithm or a deep learning algorithm, but is not limited thereto.

The process of generating the power consumption control scheme for each device group by the power consumption control device 102 is similar to the process of generating the power consumption control scheme for each physical device, except that some data used in the scheme generation process may be different, and the related process may be relatively complex, but basically implemented or the principle is the same, so that the detailed description is omitted here, and the process can be implemented by analogy with the related content in the foregoing embodiments.

Here, in the above embodiment, the technical solution of the embodiment of the present application is described by taking the machine room system 100 as an example, but the invention is not limited thereto. The technical scheme of the embodiment of the application can also be applied to environments comprising a plurality of physical devices, such as a data center system, a cluster and the like. Of course, the technical solution of the embodiment of the present application is also applicable to a single physical device.

Fig. 2 is a schematic structural diagram of a data center system according to an exemplary embodiment of the present application. As shown in fig. 2, the data center system 200 includes: at least one machine room 201 and a power consumption control device 202. Wherein each room 201 comprises at least one physical device 203. The number of physical devices included in each machine room 201 may be one or more.

The machine room 201 in this embodiment is similar to the machine room in the embodiment shown in fig. 1a, and for the related description of the physical device 203 and the machine room 201, reference may be made to the description in the embodiment shown in fig. 1a, and details are not repeated here.

This embodiment differs from the embodiment shown in fig. 1a in that: the power consumption control device 202 does not belong to a certain machine room, but belongs to the whole data center system 200, and a power consumption control scheme needs to be provided for the physical devices 203 in each machine room 201. Although the power consumption control device 202 does not belong to any computer room, in physical deployment, it may be deployed in a certain computer room, or may be deployed outside each computer room independently.

Similarly, the power consumption control device 202 in this embodiment may dynamically update the power consumption control scheme of each physical device by taking the physical device as a unit, or may dynamically update the power consumption control scheme of each device group by taking the device group as a unit.

The manner in which the power consumption control device 202 dynamically updates the power consumption control scheme for each physical device 203 is the same or similar for the case of physical device units. The function of the power consumption control apparatus 202 will be described by taking the target apparatus as an example. The power consumption control device 202 is configured to obtain relevant parameters of the target device, where the relevant parameters include power consumption index data of the target device in a historical period; predicting power consumption index data of the target equipment in a future time period according to the power consumption index data of the target equipment in a historical time period; generating a power consumption control scheme used by the target device in the future time period according to the power consumption index data of the target device in the future time period, and providing the power consumption control scheme for the target device to perform power consumption control in the future time period; the target device is any one of at least one physical device.

The function of the power consumption control apparatus 202 will be described for the case of the unit of the apparatus group. The power consumption control device 202 is configured to obtain relevant parameters of a device group, where the relevant parameters of the device group include power consumption index data of the device group in a historical period; predicting power consumption index data of the equipment group in a future period according to the power consumption index data of the equipment group in a historical period; and generating a power consumption control scheme used by the device group in the future period according to the power consumption index data of the device group in the future period.

It should be noted that, in the data center system 200, the physical devices in one device group may come from the same machine room, or may come from different machine rooms (i.e., cross machine rooms), which is not limited herein.

For a detailed process of the power consumption control device 202 dynamically updating the power consumption control scheme of the target device or device group, reference may be made to the foregoing embodiments, and details are not described herein again.

In addition to the above embodiments of the machine room system and the data center system, the present application also provides some method embodiments, which are described below.

Fig. 3a is a schematic flowchart of a power consumption control method according to an exemplary embodiment of the present disclosure. The method is described from the perspective of a device requiring power consumption control. As shown in fig. 3a, the method comprises:

31a, receiving a newly arrived first power consumption control scheme.

32a, replacing the currently used second power consumption control scheme with the first power consumption control scheme.

And 33a, controlling the power consumption of the equipment according to the first power consumption control scheme.

In this embodiment, the power consumption control scheme used by the device is dynamically updated. Alternatively, these dynamically updated power consumption control schemes may come from a power consumption control device, which is a device responsible for dynamically providing a power consumption control scheme for a physical device requiring power consumption control, such as power consumption control scheme 102 or 202 in the foregoing embodiments.

In the embodiment, the new power consumption control scheme is used for covering the old power consumption control scheme whenever the new power consumption control scheme arrives, and the method is simple and easy to implement.

For convenience of description and distinction, a newly arrived power consumption control scheme is referred to as a first power consumption control scheme, and a power consumption control scheme currently used by a device is referred to as a second power consumption control scheme. Wherein the first power consumption control scheme and the second power consumption control scheme both comprise: trigger conditions and power consumption control methods. The trigger conditions and power consumption control methods in different power consumption control schemes are different.

Optionally, one embodiment of step 33a comprises: monitoring whether a trigger condition in a first power consumption control scheme is met; and under the condition that the trigger condition in the first power consumption control scheme is met, performing power consumption control on the equipment by using a power consumption control method corresponding to the met trigger condition in the first power consumption control scheme.

Further optionally, in the process of performing power consumption control on the device according to the first power consumption control scheme, actual performance index data of the device, such as actual QoS data, may also be monitored; and the control strength of the first power consumption control scheme can be adjusted according to the actual performance index data of the equipment.

For example, actual performance data of the device may be compared to a specified performance lower limit; and if the actual performance data of the equipment is smaller than the designated performance lower limit value, shutting down the first power consumption control scheme until the actual performance index data of the equipment is larger than or equal to the designated performance lower limit value.

For another example, actual performance data of the device may be compared to a specified lower performance limit; if the actual performance data of the equipment is smaller than the specified performance lower limit value, the power consumption control method in the first power consumption control scheme is adjusted to be the power consumption control method with lower control intensity until the actual performance index data of the equipment is larger than or equal to the specified performance lower limit value.

Wherein the specified lower performance limit may be a lower performance limit that is acceptable to the device. Alternatively, in the case where the first power consumption control scenario includes a performance index data range corresponding to the trigger condition, the specified performance lower limit value may be a lower limit value of the performance index data range in the first power consumption control scenario.

In the above embodiment, the power consumption of the device is controlled by combining the actual performance index data of the device, which not only can save energy consumption, but also can ensure the service quality of the device.

Fig. 3b is a schematic flowchart of another power consumption control method according to an exemplary embodiment of the present disclosure. The method is described from the perspective of a device requiring power consumption control. As shown in fig. 3b, the method comprises:

31b, receiving a newly arrived first power consumption control scheme.

And 32b, obtaining a third power consumption control scheme according to the first power consumption control scheme and the currently used second power consumption control scheme.

And 33b, replacing the currently used second power consumption control scheme with a third power consumption control scheme, and controlling the power consumption of the equipment according to the third power consumption control scheme.

In this embodiment, whenever a new power consumption control scheme arrives, the new power consumption control scheme is merged with the old power consumption control scheme, and power consumption control is performed based on the merged power consumption control scheme. The power consumption control scheme in the mode is more perfect, and the power consumption control method is favorable for improving the power consumption control strength and improving the energy-saving effect of power consumption control.

In one manner of step 32b, the first power consumption control scheme and the second power consumption control scheme may be directly merged to obtain a third power consumption control scheme.

In another manner of step 32b, the trigger condition in the first power consumption control scheme may be compared with the trigger condition in the second power consumption control scheme; if the triggering condition in the first power consumption control scheme is different from the triggering condition in the second power consumption control scheme in type, combining the first power consumption control scheme and the second power consumption control scheme to obtain a third control scheme; and if the triggering condition in the first power consumption control scheme is the same as the triggering condition in the second power consumption control scheme in category, the old power consumption control scheme is covered by the new power consumption control scheme, namely the first power consumption control scheme is used as a third control scheme.

The third power consumption control scheme includes a trigger condition and a power consumption control method, and there may be a combination of multiple sets of trigger conditions and power consumption control methods. Based on this, the power consumption control of the device according to the third power consumption control scheme includes: and under the condition that the trigger condition in the third power consumption control scheme is met, performing power consumption control on the equipment by using a power consumption control method corresponding to the met trigger condition in the third power consumption control scheme.

Further optionally, in the process of performing power consumption control on the device according to the third power consumption control scheme, actual performance index data of the device, for example, actual QoS data, may also be monitored; and the control strength of the third power consumption control scheme can be adjusted according to the actual performance index data of the equipment.

For example, actual performance data of the device may be compared to a specified performance lower limit; and if the actual performance data of the equipment is less than the specified performance lower limit value, stopping the third power consumption control scheme until the actual performance index data of the equipment is greater than or equal to the specified performance lower limit value.

As another example, actual performance data of the device may be compared to a specified performance lower limit; and if the actual performance data of the equipment is smaller than the specified performance lower limit value, adjusting the power consumption control method in the third power consumption control scheme to be the power consumption control method with lower control intensity until the actual performance index data of the equipment is larger than or equal to the specified performance lower limit value.

Wherein the specified lower performance limit may be a lower performance limit that is acceptable to the device. Alternatively, in the case where the third power consumption control scheme includes the performance index data range corresponding to the trigger condition, the specified performance lower limit value may be a lower limit value of the performance index data range in the third power consumption control scheme.

In this embodiment, the power consumption of the device is controlled by combining the actual performance index data of the device, which not only saves the energy consumption, but also ensures the service quality of the device.

Fig. 4a is a schematic flowchart of a power consumption control scheme generation method according to an exemplary embodiment of the present application. As shown in fig. 4a, the method comprises:

41a, obtaining relevant parameters of the target device, wherein the relevant parameters comprise power consumption index data of the target device in a historical period.

And 42a, predicting the power consumption index data of the target device in a future period according to the power consumption index data of the target device in the historical period.

And 43a, generating a power consumption control scheme used by the target device in the future period according to the power consumption index data of the target device in the future period.

For the description of the steps in this embodiment, reference may be made to the foregoing embodiments, which are not repeated herein.

In this embodiment, artificial intelligence is introduced, and the power consumption control scheme of the target device can be dynamically updated through the artificial intelligence, so that the target device can realize dynamic power consumption control, and the energy-saving effect of power consumption control is improved. The target device in this embodiment may be any physical device in the computer room system, may also be any physical device in the data center system, may also be any physical device in other clusters, and may also be an independent certain physical device.

Fig. 4b is a schematic flowchart of another power consumption control scheme generation method according to an exemplary embodiment of the present application. As shown in fig. 4b, the method comprises:

and 41b, acquiring relevant parameters of the target device, wherein the relevant parameters comprise power consumption index data of the target device in a historical period and device parameters of the target device.

42b, identifying whether the target equipment belongs to equipment of which the power consumption change meets the rule requirement or not according to the equipment parameters of the target equipment and the power consumption index data of the target equipment in the historical time period; if yes, go to step 43b; if the recognition result is negative, step 45b is executed.

And 43b, predicting the power consumption index data of the target device in the future period according to the power consumption index data of the target device in the historical period, and executing the step 44b.

And 44b, generating a power consumption control scheme used by the target device in the future time period according to the power consumption index data of the target device in the future time period, and ending the operation.

And 45b, setting a default power consumption control scheme for the target equipment, and finishing the operation.

Compared with the embodiment shown in fig. 4a, the present embodiment introduces device parameters of the target device for classifying the target device; if the target equipment belongs to equipment of which the power consumption change meets the rule requirement, predicting the operation of the power consumption index data of the target equipment in a future time period according to the power consumption index data of the target equipment in a historical time period; if the target device does not belong to a device whose power consumption change meets the rule requirement, a default power consumption control scheme, such as DVFS, may be set for the target device. By classifying the target equipment, the accuracy of the prediction result is improved, a more appropriate power consumption control scheme can be generated for the target equipment, and the energy-saving effect of power consumption control is improved.

Fig. 4c is a schematic flowchart of another power consumption control scheme generation method according to an exemplary embodiment of the present application. As shown in fig. 4c, the method comprises:

and 41c, acquiring relevant parameters of the target device, wherein the relevant parameters comprise device parameters of the target device, power consumption index data and performance index data of the target device in a historical period.

42c, identifying whether the target equipment belongs to equipment of which the power consumption change meets the rule requirement or not according to the equipment parameters of the target equipment and the power consumption index data of the target equipment in the historical period; if yes, go to step 43c; if the recognition result is negative, go to step 45c.

And 43c, predicting the power consumption index data of the target device in the future period according to the power consumption index data and the performance index data of the target device in the historical period, and executing the step 44c.

And 44c, generating a power consumption control scheme used by the target device in the future time period according to the power consumption index data of the target device in the future time period, and ending the operation.

And 45c, setting a default power consumption control scheme for the target equipment, and finishing the operation.

Compared with the embodiment shown in fig. 4b, in the embodiment, performance index data of the target device in a historical time period is introduced, and meanwhile, power consumption index data of the target device in a future time period is combined to predict the power consumption index data of the target device in the future time period, so that the influence of the performance index data on the power consumption index data can be considered, the accuracy of a prediction result is improved, a more reasonable power consumption control scheme can be generated for the target device, and the accuracy of power consumption control is improved.

In the above embodiments shown in fig. 4b and 4c, one implementation of step 42b or step 42c includes: and inputting the device parameters of the target device and the power consumption index data of the target device in the historical period into the classification model to obtain whether the target device belongs to the classification result of the device with the power consumption change meeting the rule requirement.

Further optionally, in the classification model, according to the device parameter of the target device, determining a reference distribution characteristic corresponding to the device type to which the target device belongs, where the reference distribution characteristic is a distribution characteristic of power consumption index data meeting a rule requirement; and classifying the target equipment according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target equipment in the historical time period to obtain whether the target equipment belongs to the classification result of the equipment with the power consumption change meeting the rule requirement.

Further optionally, an embodiment of classifying the target device according to the reference distribution characteristic and the distribution characteristic of the power consumption index data of the target device in the historical period includes: and classifying the target equipment by adopting a logistic regression algorithm or a random forest algorithm according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target equipment in the historical time period so as to obtain whether the target equipment belongs to the classification result of the equipment with the power consumption change meeting the rule requirement.

In the above embodiments shown in fig. 4 a-4 c, one implementation of step 42a, step 43b or step 43c includes: and taking the power consumption index data of the target equipment in the historical time period or the power consumption index data and the performance index data of the target equipment in the historical time period as parameters, and inputting the parameters into a prediction model to obtain the power consumption index data of the target equipment in the future time period.

Further optionally, inside the prediction model, according to the power consumption index data of the target device in the historical time period, a linear regression algorithm or a deep learning algorithm is adopted to predict the power consumption index data of the target device in the future time period.

In the above embodiments shown in fig. 4 a-4 c, one implementation of step 42c, step 44b or step 44c includes: determining matched target trigger conditions in preset trigger conditions according to power consumption index data of the target equipment in a future time period; acquiring a target power consumption control method adaptive to a target trigger condition; and generating a power consumption control scheme used by the target device in a future period according to the target trigger condition and the target power consumption control method.

Further optionally, the determining the matched target trigger condition in the preset trigger conditions according to the power consumption index data of the target device in the future time period includes at least one of the following manners:

according to the time range corresponding to the future time period, determining the trigger condition of which the represented time range falls in the time range corresponding to the future time period from the preset trigger conditions representing the time range as a target trigger condition;

according to the power consumption index data of the target device in the future period, the trigger condition that the indicated power consumption index data range appears in the power consumption index data of the target device in the future period is determined from the preset trigger conditions indicating the power consumption index data range and serves as the target trigger condition.

Further optionally, an embodiment of the method for obtaining target power consumption control adaptive to the target trigger condition includes: and acquiring a preset power consumption control method corresponding to the target trigger condition as a target power consumption control method.

Further optionally, another embodiment of the method for obtaining the target power consumption control adapted to the target trigger condition includes: simulating the energy-saving effect of various power consumption control methods under the target triggering condition; and selecting a power consumption control method with the energy-saving effect meeting the energy-saving requirement from the energy-saving effects of various power consumption control methods under the target trigger condition as a target power consumption control method.

Further optionally, an embodiment of the foregoing generating, according to the target trigger condition and the target power consumption control method, a power consumption control scheme used by the target device in a future time period includes: acquiring a preset target performance index data range corresponding to a target trigger condition; and generating a power consumption control scheme used by the target equipment in a future time period according to the target trigger condition, the target power consumption control method and the target performance index data range.

In the above embodiments shown in fig. 4 a-4 c, one implementation of step 41a, step 41b or step 41c includes: if the target equipment is IT equipment, acquiring at least one of internal temperature, power consumption, CPU frequency and CPU load of the target equipment in a historical period as power consumption index data of the target equipment in the historical period; and if the target equipment is air conditioning equipment for cooling IT equipment, acquiring at least one of the frequency of a compressor, the rotating speed of a fan, the return air temperature and the outlet air temperature of the target equipment in a historical time period as power consumption index data of the target equipment in the historical time period.

Further optionally, in a case that the target device is an IT-class device, the method further includes: and acquiring the power consumption of other equipment associated with the target equipment in the historical period as the power consumption index data of the target equipment in the historical period.

In the embodiments shown in fig. 4a to 4c, after the power consumption control scheme used by the target device in the future period is generated, the power consumption control scheme used by the target device in the future period may also be provided to the target device for the target device to perform power consumption control in the future period. For the process of performing power consumption control by the target device according to the new power consumption control scheme, reference may be made to the description of the embodiment shown in fig. 3a or fig. 3b, which is not described herein again.

Fig. 4d is a schematic flowchart of a power consumption prediction method according to an exemplary embodiment of the present disclosure. As shown in fig. 4d, the method comprises:

41d, relevant parameters of the target device are obtained, and the relevant parameters comprise power consumption index data of the target device in a historical period.

And 42d, predicting the power consumption index data of the target device in a future period according to the power consumption index data of the target device in the historical period.

In the embodiment, artificial intelligence is introduced, the power consumption index data of the target device can be dynamically predicted through the artificial intelligence, an accurate data base can be provided for other operations depending on the power consumption index data of the target device, and the improvement of the effect of other operations is facilitated.

In an optional embodiment, the relevant parameters of the target device further comprise device parameters of the target device. Based on this, the method further includes, before predicting the power consumption index data of the target device in a future period from the power consumption index data of the target device in the history period: identifying whether the target equipment belongs to equipment of which the power consumption change meets the rule requirement or not according to the equipment parameters of the target equipment and the power consumption index data of the target equipment in the historical time period; if the target device belongs to a device with power consumption change meeting the rule requirement, the operation of predicting the power consumption index data of the target device in the future time period according to the power consumption index data of the target device in the historical time period is executed.

In an optional embodiment, an implementation manner of classifying the target device according to the device parameter of the target device and the power consumption index data of the target device in the historical period includes: and inputting the device parameters of the target device and the power consumption index data of the target device in the historical period into the classification model to obtain whether the target device belongs to the classification result of the device with the power consumption change meeting the rule requirement.

Further optionally, predicting power consumption index data of the target device in a future period according to the power consumption index data of the target device in a historical period includes: and inputting the power consumption index data of the target device in the historical time period into the prediction model to obtain the power consumption index data of the target device in the future time period.

Further optionally, the relevant parameters of the target device further include performance indicator data of the target device in a historical period. Based on this, the method for inputting the power consumption index data of the target device in the historical period into the prediction model to obtain the power consumption index data of the target device in the future period comprises the following steps: and inputting the power consumption index data of the target device in the historical period and the performance index data of the target device in the historical period into a prediction model to obtain the power consumption index data of the target device in a future period.

The prediction model may use a linear regression algorithm or a deep learning algorithm, which is not limited in this respect.

Further optionally, after predicting the power consumption index data of the target device in the future period, a power consumption control scheme used by the target device in the future period may be generated according to the power consumption index data of the target device in the future period. For how to generate the power consumption control scheme used by the target device in the future time period according to the power consumption index data of the target device in the future time period, reference may be made to the description of the foregoing embodiments, and details are not repeated here.

It should be noted that the execution subjects of the steps of the methods provided in the above embodiments may be the same device, or different devices may be used as the execution subjects of the methods. For example, the execution subjects of steps 31a to 33a may be device a; for another example, the execution subject of

steps

31a and 32a may be device a, and the execution subject of step 33a may be device B; and so on.

In addition, in some of the flows described in the above embodiments and the drawings, a plurality of operations are included in a specific order, but it should be clearly understood that the operations may be executed out of the order presented herein or in parallel, and the sequence numbers of the operations, such as 31a, 32a, etc., are merely used for distinguishing various operations, and the sequence numbers themselves do not represent any execution order. Additionally, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first", "second", etc. in this document are used for distinguishing different messages, devices, modules, etc., and do not represent a sequential order, nor limit the types of "first" and "second" to be different.

Fig. 5a is a schematic structural diagram of a computing device according to an exemplary embodiment of the present application. As shown in fig. 5a, the computing device includes: a memory 51a and a processor 52a.

The memory 51a is used for storing computer programs and may be configured to store other various data to support operations on the computing device. Examples of such data include instructions, messages, pictures, videos, etc. for any application or method operating on a computing device.

A processor 52a, coupled to the memory 51a, for executing the computer program in the memory 51a for: acquiring relevant parameters of target equipment, wherein the relevant parameters comprise power consumption index data of the target equipment in a historical period; predicting power consumption index data of the target equipment in a future time period according to the power consumption index data of the target equipment in a historical time period; and generating a power consumption control scheme used by the target device in the future period according to the power consumption index data of the target device in the future period.

The target device is a physical device that needs to perform power consumption control, and may be any physical device in a computer room system, or any physical device in a data center system, or any physical device in a cluster, or an independent physical device.

In an optional embodiment, the relevant parameters of the target device further comprise device parameters of the target device. Based on this, the processor 52a is further configured to: before predicting the power consumption index data of the target equipment in a future time period, identifying whether the target equipment belongs to equipment of which the power consumption change meets the rule requirement or not according to the equipment parameters of the target equipment and the power consumption index data of the target equipment in a historical time period; and under the condition that the target equipment belongs to equipment of which the power consumption change meets the rule requirement, the operation of predicting the power consumption index data of the target equipment in the future time period according to the power consumption index data of the target equipment in the historical time period is executed.

In an optional embodiment, when classifying the target device, the processor 52a is specifically configured to: and inputting the device parameters of the target device and the power consumption index data of the target device in the historical period into the classification model to obtain whether the target device belongs to the classification result of the device with the power consumption change meeting the rule requirement.

Further optionally, when obtaining a classification result of whether the target device belongs to a device whose power consumption change meets a rule requirement, the processor 52a is specifically configured to: determining a reference distribution characteristic corresponding to the type of the equipment to which the target equipment belongs according to the equipment parameters of the target equipment in the classification model, wherein the reference distribution characteristic is the distribution characteristic of power consumption index data meeting the rule requirement; and classifying the target equipment according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target equipment in the historical period so as to obtain the classification result of whether the target equipment belongs to the equipment of which the power consumption change meets the rule requirement.

Further optionally, when classifying the target devices according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target devices in the historical period, the processor 52a is specifically configured to: and classifying the target equipment by adopting a logistic regression algorithm or a random forest algorithm according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target equipment in the historical time period so as to obtain whether the target equipment belongs to the classification result of the equipment with the power consumption change meeting the rule requirement.

In an optional embodiment, the processor 52a, when predicting the power consumption index data of the target device in the future period, is specifically configured to: and inputting the power consumption index data of the target equipment in the historical time period into the prediction model to obtain the power consumption index data of the target equipment in the future time period.

Further optionally, the processor 52a is specifically configured to: and in the prediction model, according to the power consumption index data of the target equipment in the historical time period, adopting a linear regression algorithm or a deep learning algorithm to predict the power consumption index data of the target equipment in the future time period.

Further optionally, the relevant parameters of the target device further include performance indicator data of the target device in a historical period. Based on this, the processor 52a is specifically configured to: and inputting the power consumption index data of the target device in the historical period and the performance index data of the target device in the historical period into a prediction model to obtain the power consumption index data of the target device in a future period.

In an optional embodiment, the processor 52a, when generating the power consumption control scheme used by the target device in the future period, is specifically configured to: determining matched target trigger conditions in preset trigger conditions according to power consumption index data of the target equipment in a future time period; acquiring a target power consumption control method adaptive to a target trigger condition; and generating a power consumption control scheme used by the target equipment in a future period according to the target trigger condition and the target power consumption control method.

Further optionally, the processor 52a is specifically configured to, when determining the matched target trigger condition in the preset trigger conditions, perform at least one of the following operations:

Further optionally, when the processor 52a obtains the target power consumption control method adapted to the target trigger condition, it is specifically configured to: and acquiring a preset power consumption control method corresponding to the target trigger condition as a target power consumption control method.

Further optionally, when the processor 52a obtains the target power consumption control method adapted to the target trigger condition, it is specifically configured to: simulating the energy-saving effect of various power consumption control methods under the target trigger condition; and selecting a power consumption control method with the energy-saving effect meeting the energy-saving requirement from the energy-saving effects of various power consumption control methods under the target trigger condition as a target power consumption control method.

Further optionally, when generating the power consumption control scheme used by the target device in the future period, the processor 52a is specifically configured to: acquiring a preset target performance index data range corresponding to a target trigger condition; and generating a power consumption control scheme used by the target equipment in a future time period according to the target trigger condition, the target power consumption control method and the target performance index data range.

In an optional embodiment, when acquiring the power consumption index data of the target device in the historical period, the processor 52a is specifically configured to: if the target equipment is IT equipment, acquiring at least one of internal temperature, power consumption, CPU frequency and CPU load of the target equipment in a historical time period as power consumption index data of the target equipment in the historical time period; and if the target equipment is air conditioning equipment for cooling IT equipment, acquiring at least one of the frequency of a compressor, the rotating speed of a fan, the return air temperature and the outlet air temperature of the target equipment in a historical time period as power consumption index data of the target equipment in the historical time period.

Further optionally, in the case that the target device is an IT-class device, the processor 52a is further configured to: and acquiring the power consumption of other equipment associated with the target equipment in the historical period as the power consumption index data of the target equipment in the historical period.

In an alternative embodiment, processor 52a is further configured to: after the power consumption control scheme used by the target device in the future period is acquired, the power consumption control scheme used by the target device in the future period is provided to the target device for power consumption control by the target device in the future period.

Further, as shown in fig. 5a, the computing device further comprises: communication component 53a, display 54a, power component 55a, audio component 56a, and the like. Only some of the components are schematically shown in fig. 5a, and the computing device is not meant to include only the components shown in fig. 5 a. In addition, depending on the implementation of the computing device, the components within the dashed box in FIG. 5a are optional components, not mandatory components. For example, when the computing device is implemented as a terminal device such as a smartphone, tablet or desktop computer, the components within the dashed box in fig. 5a may be included; when the computing device is implemented as a server-side device such as a conventional server, a cloud server, a data center, or an array of servers, the components within the dashed box in fig. 5a may not be included.

The computing device provided by the embodiment abstracts power control into a scheme, dynamically updates the power control scheme of each physical device through artificial intelligence, realizes dynamic power consumption control, enables the power consumption control to be accurate to each physical device, and enables different physical devices to carry out power consumption control schemes adaptive to the power consumption conditions of the different physical devices, so that not only can the accuracy of power consumption control be improved, but also the overall energy-saving effect of the power consumption control can be improved.

Accordingly, the present application further provides a computer-readable storage medium storing a computer program, where the computer program can implement the steps in the method embodiments shown in fig. 4a to 4c when executed.

Fig. 5b is a schematic structural diagram of another computing device according to an exemplary embodiment of the present application. As shown in fig. 5b, the computing device includes: a memory 51b and a processor 52b.

The memory 51b is used to store computer programs and may be configured to store various other data to support operations on the computing device. Examples of such data include instructions, messages, pictures, videos, etc. for any application or method operating on a computing device.

A processor 52b, coupled to the memory 51b, for executing computer programs in the memory 51b for: acquiring relevant parameters of an equipment group, wherein the relevant parameters comprise power consumption index data of the equipment group in a historical period, and the equipment group comprises at least one piece of physical equipment; predicting power consumption index data of the equipment group in a future period according to the power consumption index data of the equipment group in a historical period; and generating a power consumption control scheme used by the device group in the future period according to the power consumption index data of the device group in the future period.

The device group comprises at least one physical device, and all the physical devices in the device group form a binding relationship and can share the same power consumption control scheme. In this embodiment, the forming manner of the device group is not limited. For example, the physical devices in the room that are relatively close to each other may be divided into a device group, or the physical devices with the same or similar load conditions may be divided into a device group, or the physical devices of the same type may be divided into a device group, or the physical devices of the same model may be divided into a device group, or the physical devices of the same manufacturer may be divided into a device group, or the physical devices in the whole room may be divided into a device group, and so on.

In an alternative embodiment, the power consumption indicator data for the device group during the historical period comprises: and power consumption index data of each physical device in the device group in a historical period. Accordingly, the predicted power consumption index data for the group of devices in the future time period includes: power consumption index data of each physical device in the device group in a future time period.

In another optional embodiment, the power consumption index data of the device group in the historical period is power consumption index data calculated according to the power consumption index data of each physical device in the device group in the historical period. The power consumption index data of the device group in the historical period can be discrete values or continuous values, and the power consumption index data of each historical moment in the historical period can be included. For example, the power consumption index data of the device group at a certain historical time may be an average value of the power consumption index data of each physical device in the device group at the same historical time, or a maximum value thereof, or a minimum value thereof, or an average value of the maximum value and the minimum value thereof, and so on. Accordingly, the power consumption index data of the device group in the future period is predicted according to the power consumption index data of the device group in the historical period, and can be discrete values or continuous values.

In an optional embodiment, the parameters related to the device group further include: device parameters of a device group. The device parameters of the device group mainly refer to some static parameters related to the physical devices themselves in the device group, such as device type, device model, device serial number, device specification, and the like. Based on this, the processor 52b is further configured to: acquiring equipment parameters of the equipment groups, and identifying whether the equipment groups belong to the equipment groups of which the power consumption changes meet the rule requirements or not according to the equipment parameters of the equipment groups and the power consumption index data of the equipment groups in the historical time period; and under the condition that the equipment group belongs to the equipment group of which the power consumption change meets the rule requirement, performing the operation of predicting the power consumption index data of the equipment group in the future time period according to the power consumption index data of the equipment group in the historical time period.

Further optionally, the processor 52b is specifically configured to: and classifying the equipment groups by adopting a classification model. The classification model can classify the equipment groups by adopting a logistic regression algorithm or a random forest algorithm so as to obtain whether the equipment groups belong to the classification result of the equipment groups with power consumption changes meeting the rule requirements.

Further optionally, the processor 52b is specifically configured to: and inputting the power consumption index data of the equipment group in the historical time period into the prediction model to obtain the power consumption index data of the equipment group in the future time period. The prediction model may employ a linear regression algorithm or a deep learning algorithm, but is not limited thereto.

Further, as shown in fig. 5b, the computing device further comprises: communications component 53b, display 54b, power component 55b, audio component 56b, and the like. Only some of the components are schematically shown in fig. 5b, and the computing device is not meant to include only the components shown in fig. 5b. In addition, depending on the implementation of the computing device, the components within the dashed box in FIG. 5b are optional components, not mandatory components. For example, when the computing device is implemented as a terminal device such as a smartphone, tablet or desktop computer, the components within the dashed box in fig. 5b may be included; when the computing device is implemented as a server-side device such as a conventional server, a cloud server, a data center, or an array of servers, the components within the dashed box in fig. 5b may not be included.

The computing device provided by the embodiment abstracts power control into a scheme, dynamically updates the power control scheme of each device group through artificial intelligence, realizes dynamic power consumption control, enables the power consumption control to be accurate to the device groups, and can carry out the power consumption control scheme adaptive to the power consumption condition of the different device groups, thereby not only improving the precision of the power consumption control, but also improving the overall energy-saving effect of the power consumption control.

Accordingly, the present application also provides a computer-readable storage medium storing a computer program, where the computer program can implement the operations in the embodiments related to the device group when executed.

Fig. 6a is a schematic structural diagram of a physical device according to an exemplary embodiment of the present application. As shown in fig. 6a, the physical device includes: memory 61a, processor 62a and communication component 63a.

The memory 61a is used for storing a computer program and may be configured to store other various data to support operations on the physical device. Examples of such data include instructions for any application or method operating on the physical device, messages, pictures, video, various power consumption schemes, and so forth.

A processor 62a, coupled to the memory 61a, for executing computer programs in the memory 61a for: receiving, by the communication component 63a, a newly arrived first power consumption control scheme; replacing the currently used second power consumption control scheme with the first power consumption control scheme; and controlling the power consumption of the equipment according to the first power consumption control scheme. The first power consumption control scheme comprises a trigger condition and a power consumption control method.

In an optional embodiment, when the processor 62a performs power consumption control on the device according to the first power consumption control scheme, specifically, the processor is configured to: and under the condition that the trigger condition in the first power consumption control scheme is met, performing power consumption control on the equipment by using a power consumption control method corresponding to the met trigger condition in the first power consumption control scheme.

In an alternative embodiment, the processor 62a is further configured to: monitoring actual performance index data of the equipment in the process of controlling the power consumption of the equipment according to the first power consumption control scheme; and adjusting the control strength of the first power consumption control scheme according to the actual performance index data of the equipment.

In an optional embodiment, when adjusting the control strength of the first power consumption control scheme, the processor 62a is specifically configured to: if the actual performance index data of the equipment is smaller than the designated performance lower limit value, shutting down the first power consumption control scheme until the actual performance index data of the equipment is larger than or equal to the designated performance lower limit value; or if the actual performance index data of the equipment is smaller than the designated performance lower limit value, adjusting the power consumption control method in the first power consumption control scheme to be the power consumption control method with lower control intensity until the actual performance index data of the equipment is larger than or equal to the designated performance lower limit value; wherein the specified lower limit of performance is a lower limit of performance that can be accepted by the device, or a lower limit of a range of performance indicator data in the first power consumption control scheme.

Further, as shown in fig. 6a, the physical device further includes: a display 64a, a power component 66a, an audio component 66a, and other components. Only some of the components are schematically shown in fig. 6a, and it is not meant that the physical device comprises only the components shown in fig. 6 a. In addition, the components within the dashed box in fig. 6a are optional components, not necessary components, according to the implementation form of the physical device. For example, when the physical device is implemented as a terminal device such as a smartphone, a tablet computer, or a desktop computer, the physical device may include the components within the dashed box in fig. 6 a; when the physical device is implemented as a server-side device such as a conventional server, a cloud server, a data center, or a server array, the components within the dashed box in fig. 6a may not be included.

The power consumption control scheme used by the physical device of the embodiment is dynamically updated, and when a new power consumption control scheme arrives, the new power consumption control scheme is used for covering the old power consumption control scheme, so that the method is simple and easy to implement.

Accordingly, the present application further provides a computer-readable storage medium storing a computer program, where the computer program can implement the steps in the method embodiment shown in fig. 3a when executed.

Fig. 6b is a schematic structural diagram of a physical device according to an exemplary embodiment of the present application. As shown in fig. 6b, the physical device includes: a memory 61b, a processor 62b and a communication component 63b.

The memory 61b is used for storing a computer program and may be configured to store other various data to support operations on the physical device. Examples of such data include instructions for any application or method operating on the physical device, messages, pictures, video, various power consumption schemes, and so forth.

A processor 62b, coupled to the memory 61b, for executing computer programs in the memory 61b for: receiving, by the communication component 63b, a newly arrived first power consumption control scheme; obtaining a third power consumption control scheme according to the first power consumption control scheme and the currently used second power consumption control scheme; and replacing the currently used second power consumption control scheme with a third power consumption control scheme, and performing power consumption control on the equipment according to the third power consumption control scheme.

In an optional embodiment, when the processor 62b obtains the third power consumption control scheme, it is specifically configured to: if the type of the trigger condition in the first power consumption control scheme is different from that of the trigger condition in the second power consumption control scheme, combining the first power consumption control scheme and the second power consumption control scheme to obtain a third control scheme; and if the triggering condition in the first power consumption control scheme is the same as the triggering condition in the second power consumption control scheme in type, taking the first power consumption control scheme as a third control scheme.

In an optional embodiment, when the processor 62b performs power consumption control on the device according to the third power consumption control scheme, it is specifically configured to: and under the condition that the trigger condition in the third power consumption control scheme is met, performing power consumption control on the equipment by using a power consumption control method corresponding to the met trigger condition in the third power consumption control scheme.

In an alternative embodiment, the processor 62b is further configured to: monitoring actual performance index data of the equipment in the process of controlling the power consumption of the equipment according to the third power consumption control scheme; and adjusting the control strength of the third power consumption control scheme according to the actual performance index data of the equipment.

In an optional embodiment, when adjusting the control strength of the third power consumption control scheme, the processor 62b is specifically configured to: if the actual performance index data of the equipment is smaller than the designated performance lower limit value, stopping the third power consumption control scheme until the actual performance index data of the equipment is larger than or equal to the designated performance lower limit value; or if the actual performance index data of the equipment is less than the specified performance lower limit value, adjusting the power consumption control method in the third power consumption control scheme to be the power consumption control method with lower control strength until the actual performance index data of the equipment is greater than or equal to the specified performance lower limit value; wherein the specified lower limit of performance is a lower limit of performance that can be accepted by the device, or a lower limit of a range of performance indicator data in the third power consumption control scheme.

Further, as shown in fig. 6b, the physical device further includes: a display 64b, a power component 66b, an audio component 66b, and the like. Only some of the components are schematically shown in fig. 6b, and it is not meant that the physical device comprises only the components shown in fig. 6 b. In addition, the components within the dashed box in fig. 6b are optional components, not necessary components, according to the implementation form of the physical device. For example, when the physical device is implemented as a terminal device such as a smartphone, a tablet computer, or a desktop computer, the physical device may include the components within the dashed box in fig. 6 b; when the physical device is implemented as a server-side device such as a conventional server, a cloud server, a data center, or a server array, the components within the dashed box in fig. 6b may not be included.

In the physical device of this embodiment, the power consumption control scheme used by the physical device is dynamically updated, and when a new power consumption control scheme arrives, the new power consumption control scheme is merged with the old power consumption control scheme, and power consumption control is performed based on the merged power consumption control scheme. The power consumption control scheme in the mode is more perfect, and the power consumption control method is favorable for improving the power consumption control strength and improving the energy-saving effect of power consumption control.

Accordingly, the present application further provides a computer-readable storage medium storing a computer program, where the computer program can implement the steps in the method embodiment shown in fig. 3b when executed.

FIG. 7 is a schematic diagram of a further computing device according to an exemplary embodiment of the present application. As shown in fig. 7, the computing device includes: a memory 71 and a processor 72.

The memory 71 is used for storing computer programs and may be configured to store other various data to support operations on the computing device. Examples of such data include instructions, messages, pictures, videos, etc. for any application or method operating on a computing device.

A processor 72, coupled to the memory 71, for executing computer programs in the memory 71 for: acquiring relevant parameters of target equipment, wherein the relevant parameters comprise power consumption index data of the target equipment in a historical period; and predicting the power consumption index data of the target device in a future period according to the power consumption index data of the target device in the historical period.

The target device is a physical device that needs to perform power consumption prediction, and may be any physical device in a computer room system, or any physical device in a data center system, or any physical device in a cluster, or an independent physical device.

In an optional embodiment, the relevant parameters of the target device further include device parameters of the target device. Based on this, the processor 72 is further configured to: before predicting power consumption index data of target equipment in a future time period, identifying whether the target equipment belongs to equipment of which the power consumption change meets the rule requirement according to equipment parameters of the target equipment and the power consumption index data of the target equipment in a historical time period; and under the condition that the target device belongs to a device of which the power consumption change meets the rule requirement, the operation of predicting the power consumption index data of the target device in a future period according to the power consumption index data of the target device in a historical period is executed.

In an alternative embodiment, the processor 72, when classifying the target device, is specifically configured to: and inputting the device parameters of the target device and the power consumption index data of the target device in the historical period into the classification model to obtain whether the target device belongs to the classification result of the device with the power consumption change meeting the rule requirement.

Further optionally, when obtaining the classification result of whether the target device belongs to a device whose power consumption change meets the rule requirement, the processor 72 is specifically configured to: determining a reference distribution characteristic corresponding to the type of the equipment to which the target equipment belongs according to the equipment parameters of the target equipment in the classification model, wherein the reference distribution characteristic is the distribution characteristic of power consumption index data meeting the rule requirement; and classifying the target equipment according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target equipment in the historical time period to obtain whether the target equipment belongs to the classification result of the equipment with the power consumption change meeting the rule requirement.

Further optionally, when classifying the target devices according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target devices in the historical period, the processor 72 is specifically configured to: and classifying the target equipment by adopting a logistic regression algorithm or a random forest algorithm according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target equipment in the historical time period so as to obtain whether the target equipment belongs to the classification result of the equipment with the power consumption change meeting the rule requirement.

In an optional embodiment, the processor 72, when predicting the power consumption index data of the target device in the future time period, is specifically configured to: and inputting the power consumption index data of the target device in the historical time period into the prediction model to obtain the power consumption index data of the target device in the future time period.

Further optionally, the processor 72 is specifically configured to: and in the prediction model, according to the power consumption index data of the target equipment in the historical time period, adopting a linear regression algorithm or a deep learning algorithm to predict the power consumption index data of the target equipment in the future time period.

Further optionally, the relevant parameters of the target device further include performance indicator data of the target device in the historical period. Based on this, the processor 72 is specifically configured to: and inputting the power consumption index data of the target device in the historical period and the performance index data of the target device in the historical period into a prediction model to obtain the power consumption index data of the target device in a future period.

In an optional embodiment, when acquiring the power consumption index data of the target device in the historical period, the processor 72 is specifically configured to: if the target equipment is IT equipment, acquiring at least one of internal temperature, power consumption, CPU frequency and CPU load of the target equipment in a historical period as power consumption index data of the target equipment in the historical period; and if the target equipment is air conditioning equipment for cooling IT equipment, acquiring at least one of the frequency of a compressor, the rotating speed of a fan, the return air temperature and the outlet air temperature of the target equipment in a historical time period as power consumption index data of the target equipment in the historical time period.

Further optionally, in case that the target device is an IT class device, the processor 72 is further configured to: and acquiring the power consumption of other equipment associated with the target equipment in the historical period as the power consumption index data of the target equipment in the historical period.

Further, as shown in fig. 7, the computing device further includes: communication components 73, display 74, power components 75, audio components 76, and the like. Only some of the components are schematically shown in fig. 7, and the computing device is not meant to include only the components shown in fig. 7. In addition, the components within the dashed box in FIG. 7 are optional components, not mandatory components, depending on the implementation of the computing device. For example, when the computing device is implemented as a terminal device such as a smartphone, tablet, or desktop computer, the components within the dashed box in fig. 7 may be included; when the computing device is implemented as a server-side device such as a conventional server, a cloud server, a data center, or an array of servers, the components within the dashed box in fig. 7 may not be included.

The computing device provided by the embodiment introduces artificial intelligence, can dynamically predict the power consumption index data of the target device through the artificial intelligence, can provide an accurate data base for other operations depending on the power index data of the target device, and is beneficial to improving the effects of other operations.

Accordingly, the present application further provides a computer-readable storage medium storing a computer program, where the computer program can implement the steps in the method embodiment shown in fig. 4d when executed.

The communication components of fig. 5 a-7 described above are configured to facilitate communication between the device in which the communication component is located and other devices in a wired or wireless manner. The device where the communication component is located can access a wireless network based on a communication standard, such as a WiFi, a 2G, 3G, 4G/LTE, 5G and other mobile communication networks, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component may further include a Near Field Communication (NFC) module, radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and the like.

The displays of fig. 5 a-7 described above include screens, which may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

The power supply components of fig. 5 a-7 described above provide power to the various components of the device in which the power supply component is located. The power components may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device in which the power component is located.

The audio components of fig. 5 a-7 described above may be configured to output and/or input audio signals. For example, the audio component includes a Microphone (MIC) configured to receive an external audio signal when the device in which the audio component is located is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may further be stored in a memory or transmitted via a communication component. In some embodiments, the audio assembly further comprises a speaker for outputting audio signals.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or apparatus comprising the element.

The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A power consumption control scheme generation method, comprising:

acquiring relevant parameters of target equipment, wherein the relevant parameters comprise power consumption index data of the target equipment in a historical period and equipment parameters of the target equipment;

determining a reference distribution characteristic corresponding to the type of the target equipment according to the equipment parameters of the target equipment, wherein the reference distribution characteristic is a distribution characteristic of power consumption index data meeting the rule requirement; classifying the target equipment according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target equipment in a historical period so as to determine that the target equipment belongs to a classification result of equipment of which the power consumption change meets the rule requirement;

predicting power consumption index data of the target device in a future period according to the power consumption index data of the target device in a historical period;

and generating a power consumption control scheme used by the target device in a future period according to the power consumption index data of the target device in the future period.

2. The method according to claim 1, before determining the reference distribution feature corresponding to the device type to which the target device belongs according to the device parameter of the target device, further comprising:

and inputting the device parameters of the target device and the power consumption index data of the target device in a historical period into a classification model, determining a reference distribution characteristic corresponding to the type of the device to which the target device belongs according to the device parameters of the target device in the classification model, and classifying the target device according to the reference distribution characteristic and the distribution characteristic of the power consumption index data of the target device in the historical period to obtain a classification result of whether the target device belongs to a device with power consumption change meeting the rule requirement.

3. The method according to claim 1, wherein classifying the target device according to the reference distribution characteristics and distribution characteristics of power consumption index data of the target device in a historical period to obtain a classification result of whether the target device belongs to a device whose power consumption changes meet regular requirements includes:

and classifying the target equipment by adopting a logistic regression algorithm or a random forest algorithm according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target equipment in the historical time period so as to obtain whether the target equipment belongs to the classification result of the equipment with the power consumption change meeting the rule requirement.

4. The method of claim 1, wherein predicting power consumption index data of the target device in a future period based on the power consumption index data of the target device in a historical period comprises:

and inputting the power consumption index data of the target device in the historical time period into a prediction model to obtain the power consumption index data of the target device in the future time period.

5. The method of claim 4, wherein the relevant parameters further include performance indicator data for the target device over a historical period of time;

inputting the power consumption index data of the target device in the historical time period into a prediction model to obtain the power consumption index data of the target device in a future time period, wherein the method comprises the following steps:

and inputting the power consumption index data of the target device in the historical period and the performance index data of the target device in the historical period into a prediction model to obtain the power consumption index data of the target device in a future period.

6. The method of claim 4, wherein inputting the power consumption index data of the target device in a historical period into a predictive model to obtain the power consumption index data of the target device in a future period comprises:

and predicting the power consumption index data of the target equipment in the future period by adopting a linear regression algorithm or a deep learning algorithm in the prediction model according to the power consumption index data of the target equipment in the historical period.

7. The method according to any one of claims 1-6, wherein generating the power consumption control scheme used by the target device in the future time period according to the power consumption index data of the target device in the future time period comprises:

determining matched target trigger conditions in preset trigger conditions according to power consumption index data of the target equipment in a future time period;

acquiring a target power consumption control method adaptive to the target trigger condition;

and generating a power consumption control scheme used by the target device in a future period according to the target trigger condition and the target power consumption control method.

8. The method of claim 7, wherein determining the matched target trigger condition of the preset trigger conditions according to the power consumption index data of the target device in the future time period comprises at least one of:

according to the time range corresponding to the future time period, determining a trigger condition with the represented time range falling in the time range corresponding to the future time period from preset trigger conditions representing the time range as a target trigger condition;

according to the power consumption index data of the target device in the future time period, determining a trigger condition, which occurs in the power consumption index data of the target device in the future time period, of the represented power consumption index data range from preset trigger conditions representing the power consumption index data range, as a target trigger condition.

9. The method of claim 8, wherein obtaining a target power consumption control method adapted to the target trigger condition comprises:

and acquiring a preset power consumption control method corresponding to the target trigger condition as the target power consumption control method.

10. The method of claim 8, wherein obtaining a target power consumption control method adapted to the target trigger condition comprises:

simulating the energy-saving effect of various power consumption control methods under the target triggering condition;

and selecting a power consumption control method with the energy-saving effect meeting the energy-saving requirement from the energy-saving effects of various power consumption control methods under the target trigger condition as the target power consumption control method.

11. The method of claim 7, wherein generating a power consumption control scheme for use by the target device for a future period of time based on the target trigger condition and the target power consumption control method comprises:

acquiring a preset target performance index data range corresponding to the target trigger condition;

and generating a power consumption control scheme used by the target equipment in a future time period according to the target trigger condition, the target power consumption control method and the target performance index data range.

12. The method of any one of claims 1-6, wherein obtaining power consumption indicator data for the target device over a historical period comprises:

if the target device is an IT device, acquiring at least one of internal temperature, power consumption, CPU frequency and CPU load of the target device in a historical period as power consumption index data of the target device in the historical period;

and if the target equipment is air conditioning equipment for cooling IT equipment, acquiring at least one of the frequency of a compressor, the rotating speed of a fan, the return air temperature and the outlet air temperature of the target equipment in a historical time period as power consumption index data of the target equipment in the historical time period.

13. The method of claim 12, wherein if the target device is an IT-class device, further comprising: and acquiring the power consumption of other equipment associated with the target equipment in a historical period as power consumption index data of the target equipment in the historical period.

14. The method of any one of claims 1-6, further comprising:

providing the target device with a power consumption control scheme used by the target device in a future time period for power consumption control by the target device in the future time period.

15. A power consumption control scheme generation method, comprising:

acquiring related parameters of an equipment group, wherein the related parameters comprise power consumption index data of the equipment group in a historical period and equipment parameters of the equipment group, and the equipment group comprises at least one piece of physical equipment;

determining a reference distribution characteristic corresponding to the type of the equipment to which the equipment group belongs according to the equipment parameters of the equipment group, wherein the reference distribution characteristic is a distribution characteristic of power consumption index data meeting the rule requirement; classifying the equipment group according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the equipment group in the historical time period so as to determine that the equipment group belongs to the classification result of the equipment with the power consumption change meeting the rule requirement;

predicting power consumption index data of the equipment group in a future time period according to the power consumption index data of the equipment group in a historical time period;

and generating a power consumption control scheme used by the equipment group in the future time period according to the power consumption index data of the equipment group in the future time period.

16. The method of claim 15, wherein the power consumption indicator data for the group of devices over the historical period comprises: power consumption index data of each physical device in the device group in a historical period; or the power consumption index data of the equipment group in the historical period is the power consumption index data calculated according to the power consumption index data of each physical equipment in the equipment group in the historical period.

17. A power consumption control method, comprising:

receiving a newly arrived first power consumption control scheme;

replacing a currently used second power consumption control scheme with the first power consumption control scheme;

performing power consumption control on the equipment according to the first power consumption control scheme;

monitoring actual performance index data of the equipment in the process of controlling the power consumption of the equipment according to the first power consumption control scheme;

if the actual performance index data of the equipment is smaller than the designated performance lower limit value, shutting down the first power consumption control scheme, or adjusting the power consumption control method in the first power consumption control scheme to be the power consumption control method with lower control intensity until the actual performance index data of the equipment is larger than or equal to the designated performance lower limit value;

wherein the specified lower limit of performance is a lower limit of performance acceptable to the device or a lower limit of a range of performance indicator data in the first power consumption control scheme.

18. The method of claim 17, wherein power consumption controlling the device according to the first power consumption control scheme comprises:

and under the condition that the trigger condition in the first power consumption control scheme is met, performing power consumption control on the equipment by using a power consumption control method corresponding to the met trigger condition in the first power consumption control scheme.

19. A power consumption control method, comprising:

receiving a newly arrived first power consumption control scheme;

obtaining a third power consumption control scheme according to the first power consumption control scheme and the currently used second power consumption control scheme;

replacing the currently used second power consumption control scheme with the third power consumption control scheme, and performing power consumption control on the equipment according to the third power consumption control scheme;

monitoring actual performance index data of the equipment in the process of carrying out power consumption control on the equipment according to the third power consumption control scheme;

if the actual performance index data of the equipment is smaller than the lower limit value of the designated performance, stopping the third power consumption control scheme, or adjusting the power consumption control method in the third power consumption control scheme to be the power consumption control method with lower control strength until the actual performance index data of the equipment is larger than or equal to the lower limit value of the designated performance;

wherein the specified lower limit of performance is a lower limit of performance acceptable to the device or a lower limit of a range of performance indicator data in the third power consumption control scheme.

20. The method of claim 19, wherein deriving a third power consumption control scheme based on the first power consumption control scheme and a currently used second power consumption control scheme comprises:

if the types of the trigger conditions in the first power consumption control scheme and the second power consumption control scheme are different, combining the first power consumption control scheme and the second power consumption control scheme to obtain a third power consumption control scheme;

and if the trigger condition in the first power consumption control scheme is the same as the trigger condition in the second power consumption control scheme in type, taking the first power consumption control scheme as the third power consumption control scheme.

21. The method of claim 19, wherein power consumption controlling the device according to the third power consumption control scheme comprises:

and under the condition that the trigger condition in the third power consumption control scheme is met, performing power consumption control on the equipment by using a power consumption control method corresponding to the met trigger condition in the third power consumption control scheme.

22. A method for power consumption prediction, comprising:

determining a reference distribution characteristic corresponding to the type of the equipment to which the target equipment belongs according to the equipment parameter of the target equipment, wherein the reference distribution characteristic is a distribution characteristic of power consumption index data meeting rule requirements; classifying the target equipment according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target equipment in the historical time period so as to determine that the target equipment belongs to a classification result of equipment with power consumption change meeting the rule requirement;

and predicting the power consumption index data of the target device in a future period according to the power consumption index data of the target device in the historical period.

23. The method according to claim 22, before determining the reference distribution feature corresponding to the device type to which the target device belongs according to the device parameter of the target device, further comprising:

24. The method of claim 22 or 23, wherein predicting power consumption index data of the target device in a future period based on the power consumption index data of the target device in a historical period comprises:

and inputting the power consumption index data of the target equipment in a historical time period into a prediction model to obtain the power consumption index data of the target equipment in a future time period.

25. The method of claim 24, wherein the relevant parameters further include performance indicator data for the target device over a historical period of time;

26. A computing device, comprising: a memory and a processor;

the memory for storing a computer program;

the processor, coupled with the memory, to execute the computer program to:

27. A computing device, comprising: a memory and a processor;

the memory for storing a computer program;

the processor, coupled with the memory, to execute the computer program to:

28. A physical device, comprising: a memory, a processor, and a communications component;

the communication component to receive a newly arrived first power consumption control scheme;

the memory for storing a computer program, the first power consumption control scheme, and a second power consumption control scheme currently in use;

the processor, coupled with the memory, to execute the computer program to:

performing power consumption control on the physical device according to the first power consumption control scheme;

monitoring actual performance index data of the physical equipment in the process of controlling the power consumption of the physical equipment according to the first power consumption control scheme;

if the actual performance index data of the physical equipment is smaller than the designated performance lower limit value, shutting down the first power consumption control scheme, or adjusting the power consumption control method in the first power consumption control scheme to be the power consumption control method with lower control intensity until the actual performance index data of the physical equipment is larger than or equal to the designated performance lower limit value;

wherein the specified lower limit of performance is a lower limit of performance acceptable to the physical device, or a lower limit of a range of performance indicator data in the first power consumption control scheme.

29. A physical device, comprising: a memory, a processor, and a communications component;

the processor, coupled with the memory, to execute the computer program to:

replacing a currently used second power consumption control scheme with the third power consumption control scheme, and performing power consumption control on the physical equipment according to the third power consumption control scheme;

monitoring actual performance index data of the physical equipment in the process of controlling the power consumption of the physical equipment according to the third power consumption control scheme;

if the actual performance index data of the physical device is smaller than the designated performance lower limit value, shutting down the third power consumption control scheme, or adjusting the power consumption control method in the third power consumption control scheme to be the power consumption control method with lower control intensity until the actual performance index data of the physical device is larger than or equal to the designated performance lower limit value;

wherein the specified lower limit of performance is a lower limit of performance acceptable to the physical device, or a lower limit of a range of performance indicator data in the third power consumption control scheme.

30. A computing device, comprising: a memory and a processor;

the memory for storing a computer program;

the processor, coupled with the memory, to execute the computer program to:

determining a reference distribution characteristic corresponding to the type of the equipment to which the target equipment belongs according to the equipment parameter of the target equipment, wherein the reference distribution characteristic is a distribution characteristic of power consumption index data meeting rule requirements; classifying the target equipment according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target equipment in a historical period so as to determine that the target equipment belongs to a classification result of equipment of which the power consumption change meets the rule requirement;

and predicting the power consumption index data of the target device in a future period according to the power consumption index data of the target device in a historical period.

31. A data center system, comprising: at least one machine room and power consumption control equipment; each machine room comprises at least one physical device;

the power consumption control device is used for acquiring relevant parameters of a target device, wherein the relevant parameters comprise power consumption index data of the target device in a historical period and device parameters of the target device; determining a reference distribution characteristic corresponding to the type of the equipment to which the target equipment belongs according to the equipment parameter of the target equipment, wherein the reference distribution characteristic is a distribution characteristic of power consumption index data meeting rule requirements; classifying the target equipment according to the reference distribution characteristics and the distribution characteristics of the power consumption index data of the target equipment in a historical period so as to determine that the target equipment belongs to a classification result of equipment of which the power consumption change meets the rule requirement; predicting power consumption index data of the target device in a future period according to the power consumption index data of the target device in a historical period; generating a power consumption control scheme used by the target device in a future period according to the power consumption index data of the target device in the future period, and providing the power consumption control scheme to the target device so as to control the power consumption of the target device in the future period; wherein the target device is any one of the at least one physical device.

32. A machine room system, comprising: the system comprises a machine room, a control unit and a power consumption control unit, wherein the machine room comprises at least one physical device and the power consumption control device;

33. A computer-readable storage medium storing a computer program, which when executed by a processor causes the processor to carry out the steps of the method according to any one of claims 1 to 25.