CN116578177A - Intelligent cooling energy-saving method, system, equipment and storage medium - Google Patents
Intelligent cooling energy-saving method, system, equipment and storage medium Download PDFInfo
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- G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
- G06F1/26—Power supply means, e.g. regulation thereof
- G06F1/32—Means for saving power
- G06F1/3203—Power management, i.e. event-based initiation of a power-saving mode
- G06F1/3206—Monitoring of events, devices or parameters that trigger a change in power modality
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
- G06F1/26—Power supply means, e.g. regulation thereof
- G06F1/32—Means for saving power
- G06F1/3203—Power management, i.e. event-based initiation of a power-saving mode
- G06F1/3234—Power saving characterised by the action undertaken
- G06F1/324—Power saving characterised by the action undertaken by lowering clock frequency
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- G06F1/26—Power supply means, e.g. regulation thereof
- G06F1/32—Means for saving power
- G06F1/3203—Power management, i.e. event-based initiation of a power-saving mode
- G06F1/3234—Power saving characterised by the action undertaken
- G06F1/3287—Power saving characterised by the action undertaken by switching off individual functional units in the computer system
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
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Abstract
The application provides an intelligent cooling and energy saving method, a system, equipment and a storage medium, wherein the method comprises the following steps: configuring services required by users, setting priority orders, and configuring temperature alarm thresholds of different grades; in response to the fact that the temperature of the nodes in the cluster reaches a first grade temperature alarm threshold, reminding a user that the temperature of the corresponding nodes is too high; responding to the condition that the node temperature in the cluster reaches a second level temperature alarm threshold, closing a process which occupies a CPU exceeding a preset value and is not provided with a service, and clearing all sub-processes and related garbage of the process; and in response to the fact that the temperature of the nodes in the cluster reaches a third-level temperature alarm threshold, adjusting the cluster to enter a cooling mode, reducing the frequency of CPU, and closing unconfigured service. The intelligent cooling processing mechanism of the storage system can reduce unnecessary energy consumption of the storage system from the source, and has active energy saving and cluster cooling effects.
Description
Technical Field
The application relates to the field of distributed storage systems, in particular to an intelligent cooling and energy-saving method, system, equipment and storage medium.
Background
In the distributed storage system, a large amount of data and calculation amount are processed every day, when the data amount is too large or the calculation amount is increased, the processing pressure of storage components such as cpu is inevitably increased, so that the overall temperature of the cluster machine is increased, and even the cluster machine encounters high-temperature weather, the situation is more serious. Once the temperature rises, besides the overall performance of the cluster is affected, the safety of components and the like of the storage cluster is further affected, and the overall high temperature of the cluster can cause damage to various components and even fire and the like, so that immeasurable loss is caused to the production of enterprises. The cooling mode to the storage cluster in the current market has at the computer lab increase fan, and air conditioner etc. carries out the whole cooling of computer lab through external mode, and this kind of mode can produce certain effect, but air conditioner and fan also need not stop the electricity, and overall cost is very high, even under the higher circumstances of meeting temperature, because need cooling by a wide margin, can need the bigger power of fan and air conditioner lower temperature, this kind of mode must additionally increase the consumption, even because whole circuit uses the electric power too high, probably lead to the power tripping operation and even the line generates heat too high and produce the conflagration, causes bigger inestimable loss. Sometimes, the power consumption is too high, so that the power failure of the machine room is required to be carried out safely, and once the power failure of the machine room affects the normal production of an enterprise, the power failure is also a great loss to the enterprise.
Disclosure of Invention
In view of the above, an object of the embodiments of the present application is to provide an intelligent cooling and energy saving method, system, computer device and computer readable storage medium, which can reduce unnecessary energy consumption of a storage system from a source through an intelligent cooling processing mechanism of the storage system, thereby achieving active energy saving and cluster cooling effects; the intelligent cooling processing mechanism of the storage system is used for identifying and processing the temperature abnormality of the system in time, so that the safety and the intellectualization of the system are enhanced; the overall stability and the safety of the storage system are enhanced, and the maintenance cost is saved to a certain extent; the method can effectively improve the industry pain point of the large-scale cluster high-temperature heat dissipation treatment, and further enhance the competitiveness of the storage product in the industry.
Based on the above objects, an aspect of the embodiments of the present application provides an intelligent cooling and energy saving method, which includes the following steps: configuring services required by users, setting priority orders, and configuring temperature alarm thresholds of different grades; in response to the fact that the temperature of the nodes in the cluster reaches a first grade temperature alarm threshold, reminding a user that the temperature of the corresponding nodes is too high; responding to the condition that the node temperature in the cluster reaches a second level temperature alarm threshold, closing a process which occupies a CPU exceeding a preset value and is not provided with a service, and clearing all sub-processes and related garbage of the process; and in response to the fact that the temperature of the nodes in the cluster reaches a third-level temperature alarm threshold, adjusting the cluster to enter a cooling mode, reducing the frequency of CPU, and closing unconfigured service.
In some embodiments, the method further comprises: and counting the related processes of different nodes in the cluster, and calculating the cpu occupancy rate and the memory occupancy rate of different functional modules.
In some embodiments, the method further comprises: and comprehensively counting the power consumption conditions of different functional modules according to the CPU occupancy rate and the memory occupancy rate of the different functional modules and the self power of the machine CPU.
In some embodiments, the method further comprises: starting a process to detect unnecessary processes and garbage in the cluster in real time, and deleting the detected unnecessary processes and garbage.
In some embodiments, the starting a process to detect unwanted processes and garbage in the cluster in real time includes: a child process of a functional module is determined to be an unwanted process in response to there being no longer running but the child process is running, or in response to the child process having ended but not being reclaimed by a parent process.
In some embodiments, the closing the unconfigured service comprises: and in response to the temperature not decreasing to the preset temperature value within the preset time after the unconfigured service is closed, sequentially closing the service with the rear priority order.
In some embodiments, the method further comprises: and responding to temperature recovery and keeping normal for a preset time period, and automatically recovering the closed service with the back priority order so as to ensure that all the services of the cluster normally run.
In another aspect of the embodiment of the present application, there is provided an intelligent cooling and energy saving system, including: the configuration module is used for configuring the service required by the user, setting priority ordering and configuring temperature alarm thresholds of different levels; the reminding module is configured to remind a user that the temperature of the corresponding node is too high in response to the fact that the temperature of the node in the cluster reaches a first level temperature alarm threshold; the closing module is configured to close the process which occupies the CPU and exceeds the preset value and is not configured with the service in response to the fact that the node temperature in the cluster reaches the second level temperature alarm threshold, and clear all sub-processes and related garbage of the process; and the adjusting module is configured to respond to the fact that the temperature of the nodes in the cluster reaches a third-level temperature alarm threshold, adjust the cluster to enter a cooling mode, reduce the frequency of the CPU and close the unconfigured service.
In yet another aspect of the embodiment of the present application, there is also provided a computer apparatus, including: at least one processor; and a memory storing computer instructions executable on the processor, which when executed by the processor, perform the steps of the method as above.
In yet another aspect of the embodiments of the present application, there is also provided a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method steps as described above.
The application has the following beneficial technical effects: the intelligent cooling treatment mechanism of the storage system can reduce unnecessary energy consumption of the storage system from the source, and has active energy saving and cluster cooling effects; the intelligent cooling processing mechanism of the storage system is used for identifying and processing the temperature abnormality of the system in time, so that the safety and the intellectualization of the system are enhanced; the overall stability and the safety of the storage system are enhanced, and the maintenance cost is saved to a certain extent; the method can effectively improve the industry pain point of the large-scale cluster high-temperature heat dissipation treatment, and further enhance the competitiveness of the storage product in the industry.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are necessary for the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application and that other embodiments may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of an embodiment of a method for intelligent cooling and energy saving provided by the application;
FIG. 2 is a flow chart of an embodiment of a method for intelligent cooling and energy saving provided by the application;
FIG. 3 is a schematic diagram of an embodiment of an intelligent cooling and energy saving system provided by the application;
FIG. 4 is a schematic hardware architecture diagram of an embodiment of a computer device for intelligent cooling and energy saving according to the present application;
fig. 5 is a schematic diagram of an embodiment of an intelligent cooling and energy-saving computer storage medium provided by the application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the following embodiments of the present application will be described in further detail with reference to the accompanying drawings.
It should be noted that, in the embodiments of the present application, all the expressions "first" and "second" are used to distinguish two entities with the same name but different entities or different parameters, and it is noted that the "first" and "second" are only used for convenience of expression, and should not be construed as limiting the embodiments of the present application, and the following embodiments are not described one by one.
In a first aspect of the embodiment of the application, an embodiment of a method for intelligently cooling and saving energy is provided. Fig. 1 is a schematic diagram of an embodiment of an intelligent cooling and energy saving method provided by the application.
As shown in fig. 1, the embodiment of the present application includes the following steps:
s1, configuring service required by a user, setting priority ordering, and configuring temperature alarm thresholds of different levels;
s2, responding to the fact that the temperature of the nodes in the cluster reaches a first level temperature alarm threshold value, and reminding a user that the temperature of the corresponding nodes is too high;
s3, responding to the fact that the node temperature in the cluster reaches a second level temperature alarm threshold, closing a process which occupies the CPU and exceeds a preset value and is not provided with a service, and clearing all sub-processes and related garbage of the process; and
and S4, responding to the fact that the temperature of the nodes in the cluster reaches a third-level temperature alarm threshold, adjusting the cluster to enter a cooling mode, reducing the frequency of CPU, and closing unconfigured service.
The embodiment of the application has a system temperature control processing mechanism in the cluster, and has the following functions: 1. the temperature of the cluster hardware system is monitored in real time, and when the temperature is too high, alarming is carried out according to different high-temperature grades to prompt the problem condition of the user machine. 2. The system can monitor which modules of the storage system consume power mainly and consume cpu in real time, and the ten modules are ranked, so that clients can more clearly see which modules consume power mainly, and the users can select to stop certain functions so as to reduce consumption and further realize the cooling effect. 3. The unnecessary processes and garbage of the cluster can be detected in real time, for example, the functions of a certain module are not operated any more, but the processes still have the functions of the certain module to be operated, and the zombie processes are released. To reduce unnecessary consumption. 4. And providing a cooling mode, and when the cluster does not operate in a certain period or is relatively idle and is not required to process some larger or important calculation, or the cluster has high-risk high temperature, starting the cooling mode to reduce the CPU frequency so as to maintain the low-energy running of the basic functions of the cluster and further reduce the machine temperature. 5. And providing a service custom module. The module can provide custom service, namely, a user can carry out priority custom setting on the functions and the services of the storage system according to own needs, a program or service with high priority can be executed preferentially, and a function with low priority occupies less resources and even does not go to run, so that unnecessary energy consumption of a cluster is reduced, and the purpose of cooling is achieved. 6. Intelligent cooling treatment mechanism with mutually matched modules. 7. Intelligent temperature recovery processes learning mechanisms. Through above-mentioned 7 parts, can reduce storage system energy consumption at the source and play the reduction and generate heat, energy-conserving cooling effect, the appropriate external physical cooling mode of cooperation reaches the effect of the benign control of cluster whole temperature.
Fig. 2 is a flowchart of an embodiment of an intelligent cooling and energy saving method provided by the application, and an embodiment of the application is described with reference to fig. 2.
And configuring the service required by the user, setting priority ordering, and configuring temperature alarm thresholds of different grades. And each node of the cluster has a timing task to detect the real-time temperature of the machine of each node, and the temperature detection mode only needs to use a command of hardware. The user can set the temperature alarm threshold in advance and can be divided into warning and serious, the high risk is divided into three alarm grades (the default threshold is 30 ℃, 35 ℃ and 40 ℃ respectively, and the user can adjust according to the actual condition of the machine room), and once a certain node machine temperature is detected to be higher than one of the three thresholds, the corresponding warning is generated to remind the user, so that the user can carry out cooling measures for processing. The user configures the needed service in advance in the service custom module and sets the priority order, if not, all the functions are according to the default priority of the system. The temperature alarm module configures three levels of temperature alarm thresholds, and one thread always exists for detecting the temperature of each node of the cluster, and different alarms are sent out when the set different levels of thresholds are reached.
And in response to the fact that the temperature of the nodes in the cluster reaches the first grade temperature alarm threshold, reminding a user that the temperature of the corresponding nodes is too high. If one or more nodes of the cluster are encountered to be elevated in temperature, the user is simply alerted to which node is too high to reach the warning level if the warning threshold is only reached at the "warning" level.
And in response to the fact that the node temperature in the cluster reaches the second level temperature alarm threshold, closing the process which occupies the service which is exceeding the preset value and is not configured, and clearing all sub-processes and related garbage of the process. If the alarm threshold of the serious level is reached, a node temperature serious level alarm is generated, at this time, the cluster energy consumption detection module closes the processes which occupy the cpu and are not in the custom priority service, and calls the garbage cleaning module to clean all sub-processes of the closed processes and related garbage.
And in response to the fact that the temperature of the nodes in the cluster reaches a third-level temperature alarm threshold, adjusting the cluster to enter a cooling mode, reducing the frequency of CPU, and closing unconfigured service. If the high-risk level alarm threshold is reached, if the cluster continues to run at a high speed, the system will crash, and even the overheat burnout of components such as cpu may be caused, at this time, a cluster node temperature high-risk level alarm will be generated first, the cluster will automatically enter a cooling mode, the frequency of cpu is reduced, and modules which are not used or are not important (i.e. the user is not in the function or service module configured by the service custom module) are closed, so that the basic important functions of the cluster are maintained to run at low energy consumption, and the machine temperature is reduced.
In some embodiments, the method further comprises: and counting the related processes of different nodes in the cluster, and calculating the cpu occupancy rate and the memory occupancy rate of different functional modules.
In some embodiments, the method further comprises: and comprehensively counting the power consumption conditions of different functional modules according to the CPU occupancy rate and the memory occupancy rate of the different functional modules and the self power of the machine CPU. The power consumption of the different functional modules is comprehensively counted by combining the power of the components such as the machine CPU and the like. The power consumption ranking of the first ten is displayed, so that a customer can more clearly know which modules are mainly in power consumption performance, and the customer can select to stop certain functions so as to reduce consumption and further play a role in cooling.
In some embodiments, the method further comprises: starting a process to detect unnecessary processes and garbage in the cluster in real time, and deleting the detected unnecessary processes and garbage.
In some embodiments, the starting a process to detect unwanted processes and garbage in the cluster in real time includes: a child process of a functional module is determined to be an unwanted process in response to there being no longer running but the child process is running, or in response to the child process having ended but not being reclaimed by a parent process. Starting a process to detect unnecessary processes and garbage of the cluster in real time, for example, a function of a certain module is no longer running, but still a child process of the module is running, or the child process is finished but not recovered by a parent process, etc., the module will recognize the corresponding process at fixed time and kill the corresponding process to reduce the data processing amount of the cpu. Thereby reducing unnecessary consumption and playing a role in cooling.
In some embodiments, the closing the unconfigured service comprises: and in response to the temperature not decreasing to the preset temperature value within the preset time after the unconfigured service is closed, sequentially closing the service with the rear priority order. The user can carry out priority custom setting on the functions and services of the storage system according to the self needs, and some functions and modules mainly used by the user are configured in the cluster configuration file, when the cluster temperature is higher, the low-priority service is closed at first, the normal operation of the key service is ensured, the unnecessary energy consumption of the cluster is further reduced, and the purpose of cooling is achieved.
When the processing modes have no obvious effect, the corresponding node is automatically put into the sleep mode, the energy consumption is lowest, the service load on the node is balanced to other nodes with lower temperature, and the minimum influence on the service is achieved. And reminds the user to take other physical cooling measures.
In some embodiments, the method further comprises: and responding to temperature recovery and keeping normal for a preset time period, and automatically recovering the closed service with the back priority order so as to ensure that all the services of the cluster normally run. If the temperature is recovered and kept normal for 1 hour, the closed low-priority service is automatically recovered, and normal operation of all the services of the cluster is ensured. By carrying out background training learning on the energy consumption and the temperature data record of the current cluster equipment, the time period and the service of the cluster equipment which are easy to cause temperature rise can be intelligently predicted, so that temperature control alarm and the processing are carried out in advance, and the influence of overhigh temperature on the equipment is prevented and reduced.
According to the embodiment of the application, through an intelligent cooling processing mechanism of the storage system, unnecessary energy consumption of the storage system can be reduced from the source, and the active energy-saving and cluster cooling effects are achieved; the intelligent cooling processing mechanism of the storage system is used for identifying and processing the temperature abnormality of the system in time, so that the safety and the intellectualization of the system are enhanced; the overall stability and the safety of the storage system are enhanced, and the maintenance cost is saved to a certain extent; the method can effectively improve the industry pain point of the large-scale cluster high-temperature heat dissipation treatment, and further enhance the competitiveness of the storage product in the industry.
It should be noted that, in the foregoing embodiments of the intelligent cooling and energy saving method, the steps may be intersected, replaced, added and subtracted, so that the method of intelligent cooling and energy saving by using these reasonable permutation and combination changes should also belong to the protection scope of the present application, and should not limit the protection scope of the present application to the embodiments.
Based on the above object, a second aspect of the embodiment of the present application provides an intelligent cooling and energy-saving system. As shown in fig. 3, the system 200 includes the following modules: the configuration module is used for configuring the service required by the user, setting priority ordering and configuring temperature alarm thresholds of different levels; the reminding module is configured to remind a user that the temperature of the corresponding node is too high in response to the fact that the temperature of the node in the cluster reaches a first level temperature alarm threshold; the closing module is configured to close the process which occupies the CPU and exceeds the preset value and is not configured with the service in response to the fact that the node temperature in the cluster reaches the second level temperature alarm threshold, and clear all sub-processes and related garbage of the process; and the adjusting module is configured to respond to the fact that the temperature of the nodes in the cluster reaches a third-level temperature alarm threshold, adjust the cluster to enter a cooling mode, reduce the frequency of the CPU and close the unconfigured service.
In some embodiments, the system further comprises a computing module configured to: and counting the related processes of different nodes in the cluster, and calculating the cpu occupancy rate and the memory occupancy rate of different functional modules.
In some embodiments, the system further comprises a statistics module configured to: and comprehensively counting the power consumption conditions of different functional modules according to the CPU occupancy rate and the memory occupancy rate of the different functional modules and the self power of the machine CPU.
In some embodiments, the system further comprises a deletion module configured to: starting a process to detect unnecessary processes and garbage in the cluster in real time, and deleting the detected unnecessary processes and garbage.
In some embodiments, the deletion module is configured to: a child process of a functional module is determined to be an unwanted process in response to there being no longer running but the child process is running, or in response to the child process having ended but not being reclaimed by a parent process.
In some embodiments, the adjustment module is configured to: and in response to the temperature not decreasing to the preset temperature value within the preset time after the unconfigured service is closed, sequentially closing the service with the rear priority order.
In some embodiments, the system further comprises a recovery module configured to: and responding to temperature recovery and keeping normal for a preset time period, and automatically recovering the closed service with the back priority order so as to ensure that all the services of the cluster normally run.
In view of the above object, a third aspect of the embodiments of the present application provides a computer device, including: at least one processor; and a memory storing computer instructions executable on the processor, the instructions being executable by the processor to perform the steps of: s1, configuring service required by a user, setting priority ordering, and configuring temperature alarm thresholds of different levels; s2, responding to the fact that the temperature of the nodes in the cluster reaches a first level temperature alarm threshold value, and reminding a user that the temperature of the corresponding nodes is too high;
s3, responding to the fact that the node temperature in the cluster reaches a second level temperature alarm threshold, closing a process which occupies the CPU and exceeds a preset value and is not provided with a service, and clearing all sub-processes and related garbage of the process; and S4, responding to the fact that the temperature of the nodes in the cluster reaches a third-level temperature alarm threshold, adjusting the cluster to enter a cooling mode, reducing the frequency of CPU, and closing the unconfigured service.
In some embodiments, the steps further comprise: and counting the related processes of different nodes in the cluster, and calculating the cpu occupancy rate and the memory occupancy rate of different functional modules.
In some embodiments, the steps further comprise: and comprehensively counting the power consumption conditions of different functional modules according to the CPU occupancy rate and the memory occupancy rate of the different functional modules and the self power of the machine CPU.
In some embodiments, the steps further comprise: starting a process to detect unnecessary processes and garbage in the cluster in real time, and deleting the detected unnecessary processes and garbage.
In some embodiments, the starting a process to detect unwanted processes and garbage in the cluster in real time includes: a child process of a functional module is determined to be an unwanted process in response to there being no longer running but the child process is running, or in response to the child process having ended but not being reclaimed by a parent process.
In some embodiments, the closing the unconfigured service comprises: and in response to the temperature not decreasing to the preset temperature value within the preset time after the unconfigured service is closed, sequentially closing the service with the rear priority order.
In some embodiments, the steps further comprise: and responding to temperature recovery and keeping normal for a preset time period, and automatically recovering the closed service with the back priority order so as to ensure that all the services of the cluster normally run.
Fig. 4 is a schematic hardware structure diagram of an embodiment of the intelligent cooling and energy-saving computer device provided by the application.
Taking the example of the apparatus shown in fig. 4, a processor 301 and a memory 302 are included in the apparatus.
The processor 301 and the memory 302 may be connected by a bus or otherwise, for example in fig. 4.
The memory 302 is used as a non-volatile computer readable storage medium for storing non-volatile software programs, non-volatile computer executable programs and modules, such as program instructions/modules corresponding to the intelligent cooling and power saving method in the embodiment of the present application. The processor 301 executes various functional applications and data processing of the server, that is, a method for realizing intelligent cooling and energy saving, by running nonvolatile software programs, instructions and modules stored in the memory 302.
Memory 302 may include a storage program area that may store an operating system, at least one application program required for functionality, and a storage data area; the storage data area may store data created according to the use of the intelligent cooling and power saving method, etc. In addition, memory 302 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, memory 302 may optionally include memory located remotely from processor 301, which may be connected to the local module via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Computer instructions 303 corresponding to one or more intelligent cooling and power saving methods are stored in memory 302 that, when executed by processor 301, perform the intelligent cooling and power saving method of any of the method embodiments described above.
Any embodiment of the computer device executing the intelligent cooling and energy saving method can achieve the same or similar effect as any corresponding embodiment of the method.
The application also provides a computer readable storage medium storing a computer program which when executed by a processor performs a method of intelligent cooling and energy saving.
Fig. 5 is a schematic diagram of an embodiment of the intelligent cooling and energy-saving computer storage medium according to the present application. Taking a computer storage medium as shown in fig. 5 as an example, the computer readable storage medium 401 stores a computer program 402 that when executed by a processor performs the above method.
Finally, it should be noted that, as will be appreciated by those skilled in the art, all or part of the processes in the methods of the embodiments described above may be implemented by a computer program to instruct related hardware, and the program of the intelligent cooling and energy saving method may be stored in a computer readable storage medium, where the program may include the processes in the embodiments of the methods described above when executed. The storage medium of the program may be a magnetic disk, an optical disk, a read-only memory (ROM), a random-access memory (RAM), or the like. The computer program embodiments described above may achieve the same or similar effects as any of the method embodiments described above.
The foregoing is an exemplary embodiment of the present disclosure, but it should be noted that various changes and modifications could be made herein without departing from the scope of the disclosure as defined by the appended claims. The functions, steps and/or actions of the method claims in accordance with the disclosed embodiments described herein need not be performed in any particular order. Furthermore, although elements of the disclosed embodiments may be described or claimed in the singular, the plural is contemplated unless limitation to the singular is explicitly stated.
It should be understood that as used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly supports the exception. It should also be understood that "and/or" as used herein is meant to include any and all possible combinations of one or more of the associated listed items.
The foregoing embodiment of the present application has been disclosed with reference to the number of embodiments for the purpose of description only, and does not represent the advantages or disadvantages of the embodiments.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program for instructing relevant hardware, and the program may be stored in a computer readable storage medium, where the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
Those of ordinary skill in the art will appreciate that: the above discussion of any embodiment is merely exemplary and is not intended to imply that the scope of the disclosure of embodiments of the application, including the claims, is limited to such examples; combinations of features of the above embodiments or in different embodiments are also possible within the idea of an embodiment of the application, and many other variations of the different aspects of the embodiments of the application as described above exist, which are not provided in detail for the sake of brevity. Therefore, any omission, modification, equivalent replacement, improvement, etc. of the embodiments should be included in the protection scope of the embodiments of the present application.
Claims (10)
1. The intelligent cooling and energy saving method is characterized by comprising the following steps:
configuring services required by users, setting priority orders, and configuring temperature alarm thresholds of different grades;
in response to the fact that the temperature of the nodes in the cluster reaches a first grade temperature alarm threshold, reminding a user that the temperature of the corresponding nodes is too high;
responding to the condition that the node temperature in the cluster reaches a second level temperature alarm threshold, closing a process which occupies a CPU exceeding a preset value and is not provided with a service, and clearing all sub-processes and related garbage of the process; and
and in response to the fact that the temperature of the nodes in the cluster reaches a third-level temperature alarm threshold, adjusting the cluster to enter a cooling mode, reducing the frequency of CPU, and closing unconfigured service.
2. The intelligent cooling and energy saving method according to claim 1, further comprising:
and counting the related processes of different nodes in the cluster, and calculating the cpu occupancy rate and the memory occupancy rate of different functional modules.
3. The intelligent cooling and energy saving method according to claim 2, further comprising:
and comprehensively counting the power consumption conditions of different functional modules according to the CPU occupancy rate and the memory occupancy rate of the different functional modules and the self power of the machine CPU.
4. The intelligent cooling and energy saving method according to claim 1, further comprising:
starting a process to detect unnecessary processes and garbage in the cluster in real time, and deleting the detected unnecessary processes and garbage.
5. The intelligent cooling and energy saving method according to claim 4, wherein starting a process to detect unwanted processes and garbage in the cluster in real time comprises:
a child process of a functional module is determined to be an unwanted process in response to there being no longer running but the child process is running, or in response to the child process having ended but not being reclaimed by a parent process.
6. The intelligent cooling and power saving method according to claim 1, wherein the closing of the unconfigured service comprises:
and in response to the temperature not decreasing to the preset temperature value within the preset time after the unconfigured service is closed, sequentially closing the service with the rear priority order.
7. The intelligent cooling and energy saving method according to claim 1, further comprising:
and responding to temperature recovery and keeping normal for a preset time period, and automatically recovering the closed service with the back priority order so as to ensure that all the services of the cluster normally run.
8. An intelligent cooling and energy saving system, comprising:
the configuration module is used for configuring the service required by the user, setting priority ordering and configuring temperature alarm thresholds of different levels;
the reminding module is configured to remind a user that the temperature of the corresponding node is too high in response to the fact that the temperature of the node in the cluster reaches a first level temperature alarm threshold;
the closing module is configured to close the process which occupies the CPU and exceeds the preset value and is not configured with the service in response to the fact that the node temperature in the cluster reaches the second level temperature alarm threshold, and clear all sub-processes and related garbage of the process; and
and the adjusting module is configured to respond to the fact that the temperature of the nodes in the cluster reaches a third-level temperature alarm threshold, adjust the cluster to enter a cooling mode, reduce the frequency of the CPU and close the unconfigured service.
9. A computer device, comprising:
at least one processor; and
a memory storing computer instructions executable on the processor, which when executed by the processor, perform the steps of the method of any one of claims 1-7.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method of any one of claims 1-7.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117148955A (en) * | 2023-10-30 | 2023-12-01 | 北京阳光金力科技发展有限公司 | Data center energy consumption management method based on energy consumption data |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117148955A (en) * | 2023-10-30 | 2023-12-01 | 北京阳光金力科技发展有限公司 | Data center energy consumption management method based on energy consumption data |
| CN117148955B (en) * | 2023-10-30 | 2024-02-06 | 北京阳光金力科技发展有限公司 | Data center energy consumption management method based on energy consumption data |
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