CN107197013B - Energy-saving system for enhancing cloud computing environment - Google Patents
Energy-saving system for enhancing cloud computing environment Download PDFInfo
- Publication number
- CN107197013B CN107197013B CN201710357258.0A CN201710357258A CN107197013B CN 107197013 B CN107197013 B CN 107197013B CN 201710357258 A CN201710357258 A CN 201710357258A CN 107197013 B CN107197013 B CN 107197013B
- Authority
- CN
- China
- Prior art keywords
- cloud computing
- computing environment
- request
- workload
- node
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Theoretical Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Power Sources (AREA)
Abstract
The invention provides an energy-saving system for enhancing cloud computing environment, which comprises: the client sends a cloud computing request and is received by the cloud computing environment platform; the cloud computing environment platform analyzes, evaluates and obtains the workload included in the request, and determines an energy-saving strategy according to the comparison of the workload; the node computing equipment receives scheduling executed by the cloud computing environment platform according to the energy-saving strategy, then executes the workload, and after computing processing is finished, transmits a processing result back to the cloud computing environment platform; and the cloud computing environment platform further sends the result of the cloud computing request to the client. The system can effectively reduce energy consumption of node processing equipment such as physical computing equipment, virtual computing equipment and the like in the cloud computing environment, further improve the efficiency of scheduling, migration and combination of the virtual machines, and enhance the safety of the cloud computing environment.
Description
Technical Field
The invention relates to the field of electric digital data processing, in particular to an energy-saving system for enhancing a cloud computing environment, and aims to reduce energy consumption of the cloud computing environment and enhance safety of the cloud computing environment.
Background
With the rapid development of information technology, especially the development of internet technology, the demand of users for computing and storing data is increased dramatically, and the traditional mode of satisfying the demand of users by purchasing a large number of high-performance servers will greatly increase the waste of resources. Cloud Computing (Cloud Computing) technology is applied, and is referred to as providing available, convenient, on-demand network access into a shared pool of configurable Computing resources including networks, servers, storage, application software, services, and the like, such that the resources can be provided quickly with little administrative effort or interaction with the service provider. As an emerging research and application field in the internet technology, the internet technology is receiving more and more attention, and has rapidly spread and become popular in recent years, because it adapts to a new computing model in which a network service is shifted from a service configuration of "high concentration, high cost, low pass use" to "high distribution, low cost, high pass use", as an emerging research and application field in the information technology, is receiving more and more attention from related enterprises and research institutions, and is regarded as a necessary trend of a future computing model. Software and hardware resources and information can be shared in a cloud computing mode and can be provided for computers and other equipment as required.
Because cloud computing is an internet-based resource which is dynamic, easy to expand and often virtualized, the computing capacity of the cloud computing is exponentially improved, and the cloud computing can perform 10 trillion times per second, so that computation of a large amount of data such as atomic energy tests and weather change forecasts can be simulated. It is due to these advantages of cloud computing that there are a number of problems in implementation: the number of node computing devices in a cloud computing environment is becoming larger and larger, and the energy consumed is increasing. For example, cloud computing devices from google, usa consume 1 billion KWh of electricity per year, which is quite large, approximately equal to the total energy consumption of a small city. Particularly, different periods of different requirements for the use of the node computing equipment are different, the use requirements in daytime and working days are large, and more node computing equipment is called; on the contrary, at night and on weekends, the use demand is small, the number of the called node computing devices is small, at the moment, if the node computing devices are in operation or are in operation delay waiting standby, energy is greatly wasted, higher energy consumption becomes a bottleneck restricting the development of cloud computing, and today advocating energy conservation and emission reduction, the state needs to be improved urgently.
For the energy saving problem of the cloud computing environment, there are many technologies, for example, the number of running servers is reduced by migrating the virtual machine, and then the energy consumption of the whole cloud computing environment is reduced. In addition, other techniques exist such as improvements to the scheduling of loads, achieving power savings by queuing or ordering, or simply giving different priorities. The results of these methods show that they have a certain energy saving effect, but also have some defects, because of the selection of parameters and the insufficiency of the calculation methods in the processes of scheduling calculation and allocation and migration and merging of virtual machines, the energy consumption control of node processing devices such as physical calculation devices and virtual calculation devices in the cloud computing environment and the efficiency of scheduling, migration and merging of virtual machines still need to be further improved, and because of the numerous node calculation devices connected in the cloud computing environment, there is a certain potential safety hazard.
Disclosure of Invention
One of the purposes of the invention is to provide an energy-saving system for enhancing a cloud computing environment, which can solve the technical problems in the prior art. The energy consumption of node processing equipment such as physical computing equipment, virtual computing equipment and the like in the cloud computing environment can be effectively reduced, the efficiency of scheduling, migration and combination of the virtual machines is further improved, and the safety of the cloud computing environment is enhanced.
The technical scheme adopted by the invention to solve the technical problems is as follows: an enhanced cloud computing environment energy saving system, comprising: the client sends a cloud computing request and is received by the cloud computing environment platform; and a cloud computing environment C comprising: the cloud computing environment platform analyzes, evaluates and obtains the workload included in the request, and determines an energy-saving strategy according to the comparison of the workload; the node computing equipment receives the scheduling executed by the cloud computing environment platform according to the energy-saving strategy, then executes the workload, and after the computing processing is finished, transmits the processing result back to the cloud computing environment platform; and the cloud computing environment platform further sends the result of the cloud computing request to the client.
According to another aspect of the invention, the enhanced cloud computing environment energy saving system further comprises: the cloud computing environment C in the enhanced cloud computing environment energy-saving system further comprises: a history database, and the cloud computing environment C is configured to: receiving, by the cloud computing environment platform, a cloud computing request sent from a client; the cloud computing environment platform carries out security authentication on the computing request, and the following operations are executed after the authentication is passed; analyzing, evaluating and acquiring the workload included in the request by the cloud computing environment platform; the cloud computing environment platform analyzes and judges whether the cloud computing request is requested to be processed or not by calling the historical database, if the cloud computing request is processed, the cloud computing environment platform directly calls a previous processing result from the historical database and sends a cloud computing request result subjected to computing processing to the client; if not previously processed, continue; updating the capacity, the capacity and the priority of each node computing device by the cloud computing environment platform; comparing, by the cloud computing environment platform, the workload included in the request with the information processing margin in the existing node computing device one by one, according to the priority of the existing node computing device; if the former is smaller than the latter, the cloud computing environment platform encrypts the workload included in the request according to the priority and then delivers the encrypted workload to the selected node computing equipment, and after the computing processing is finished, the encrypted workload is delivered back to the cloud computing environment platform; then, the following decryption is performed; if the former is larger than the latter, the cloud computing environment platform configures the host and the virtual machine in the node computing equipment and/or migrates and/or combines the virtual machine to reduce the total number of the used node computing equipment, encrypts the workload included in the request and delivers the encrypted workload to the selected node computing equipment, and after the computing processing is finished, delivers the encrypted workload to the cloud computing environment platform; then, the following decryption is performed; decrypting, by the cloud computing environment platform, the data; and sending the result of the cloud computing request subjected to computing processing to the client by the cloud computing environment platform.
According to another aspect of the invention, the enhanced cloud computing environment energy saving system further comprises: the node computing device in the enhanced cloud computing environment energy-saving system is configured to: identifying a virtual machine to be migrated in the case that a workload included in the request is greater than an information processing margin in the existing node computing device; obtaining the use parameters Par of the central processing unit of the host i to be tested to be migratediThe parameter PariThe sum is the quadratic sum of the difference between the currently processed workload of the central processor of host i and the host distribution mean, and then the quotient of the sum and the number of hosts, i.e.:
wherein represents the current processing workload of the central processing unit of host i, B represents the host distribution average, and M represents the number of hosts, which is a positive integer of at least 2; repeating the previous operation for the same virtual machine to be migrated until M hosts; for the jth virtual machine to be migrated, repeating the previous two steps until M hosts, and repeating the execution until N virtual machines to be migrated, namely executing M (N-1) times, wherein N represents the number of the virtual machines to be migrated, and the value of N is a positive integer of at least 2; for each virtual machine to be migrated and each host, an array Ary of central processor usage parameters is created:
selecting the minimum from each row, creating an array of minima of use parameters Ary of the central processorMIN，
Computing AryMINCorresponding to the preferred migratable virtual machine and the preferred host, and performs a scheduled allocation migration.
According to another aspect of the invention, the enhanced cloud computing environment energy saving system further comprises: the node computing device in the enhanced cloud computing environment energy-saving system is configured to: under the condition that the workload included in the request is larger than the information processing allowance in the existing node computing equipment, calculating the number of virtual machines with unit processing capacity to be scheduled according to the workload included in the request; decomposing a plurality of virtual machines of unit processing capacity to be scheduled into groups; determining whether the virtual machine needs to be migrated according to the number of the packets; if the critical value is exceeded, the requirement is needed, otherwise, the requirement is not needed; if the node computing equipment in the low power consumption state is enough, migrating the virtual machine in the previous step to the node computing equipment in the low power consumption state according to the performances and capacities of a central processing unit, a static memory and a dynamic memory of the node computing equipment in the low power consumption state; if the data is insufficient, according to the performances and capacities of a central processing unit, a static memory and a dynamic memory of the node computing equipment in the low power consumption state, the signing performance and capacity are divided by the unit processing capacity, and data of an integral number of unit processing capacities are transmitted to the node computing equipment in the low power consumption state by adopting a rounding and tailing removing method.
According to another aspect of the invention, wherein the low power consumption state comprises a sleep, standby, running to a delayed wait state.
According to another aspect of the present invention, wherein the calculating the number of virtual machines of the unit processing capacity to be scheduled according to the workload included in the request further comprises: the number is obtained in the following manner
Wherein DkRepresenting the number of virtual machines, EkA numerical value representing the amount of tasks of the virtual machine, and E representing the number of servers.
According to another aspect of the invention, the enhanced cloud computing environment energy saving system further comprises: the client comprises a user, a desktop or portable PC, a terminal with PC functionality or a user equipment UE in communication technology.
According to another aspect of the invention, the enhanced cloud computing environment energy saving system further comprises: the cloud computing environment platform firstly identifies the information type in the request, removes the request header information in the request, and reserves, evaluates and acquires the information to be processed in the request.
According to another aspect of the invention, the enhanced cloud computing environment energy saving system further comprises: the priority of the existing node computing device is determined based on the performance and capacity of a central processor, a static memory and a dynamic memory of the node computing device, and the parameters are updated to the cloud computing environment platform regularly.
According to another aspect of the invention, the enhanced cloud computing environment energy saving system further comprises: the information processing margin in the existing node computing device is obtained by subtracting the workload at the current time point from a preset threshold of the existing node computing device, wherein the preset threshold is a ratio obtained by multiplying the total performance and capacity of the node computing device by a certain ratio, and the ratio is at least 80%.
The energy-saving system for enhancing the cloud computing environment can effectively reduce energy consumption of node processing equipment such as physical computing equipment and virtual computing equipment in the cloud computing environment, further improve the efficiency of scheduling, migration and combination of virtual machines, and enhance the safety of the cloud computing environment.
Drawings
Embodiments of the invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements and in which:
FIG. 1 illustrates a method for enhancing energy savings in a cloud computing environment, according to an exemplary embodiment of the present invention;
FIG. 2 illustrates a schematic diagram of an enhanced cloud computing environment energy saving system, according to an exemplary embodiment of the present invention;
FIG. 3 illustrates a flow diagram of a method for enhancing energy savings in a cloud computing environment, according to an exemplary embodiment of the present invention;
FIG. 4 illustrates a flow diagram of a process for configuring and/or migrating and/or combining virtual machines in a node computing device to reduce the total number of node computing devices used and computing processes, according to an exemplary embodiment of the present invention;
FIG. 5 illustrates an alternative flow diagram of a process for configuring and/or migrating and/or combining virtual machines in a node computing device to reduce the total number of node computing devices used and to compute, according to an exemplary embodiment of the invention; and
fig. 6 illustrates an energy saving effect diagram of the present invention with respect to the prior art, according to an exemplary embodiment of the present invention.
Detailed Description
In the following description, reference is made to the accompanying drawings that show, by way of illustration, several specific embodiments. It will be understood that: other embodiments are contemplated and may be made without departing from the scope or spirit of the present disclosure. The following detailed description is, therefore, not to be taken in a limiting sense.
According to an exemplary embodiment of the invention, fig. 1 illustrates a method for enhancing energy saving of a cloud computing environment, comprising the following steps:
receiving a cloud computing request sent from a client;
the cloud computing environment platform analyzes, evaluates and acquires the workload included in the request;
according to the comparison of the workload, determining an energy-saving strategy and scheduling resources to execute the workload, and after the calculation processing is finished, delivering the workload back to the cloud computing environment platform; and
and the cloud computing environment platform sends the result of the cloud computing request to the client.
FIG. 2 illustrates a schematic diagram of an enhanced cloud computing environment energy saving system, according to an exemplary embodiment of the present invention. Wherein the system contains a client 1, and a cloud computing environment C for communicating and interacting with the client 1. The cloud computing environment C includes a cloud computing environment platform 1 and a plurality of node computing devices 2-6. The cloud computing environment platform 1 can reasonably call the node computing devices, and after optimization, a small number of node computing devices can be used for reducing the energy consumption of the whole system.
Accordingly, the enhanced cloud computing environment energy saving system comprises:
the client sends a cloud computing request and is received by the cloud computing environment platform; and
a cloud computing environment C comprising:
the cloud computing environment platform analyzes, evaluates and obtains the workload included in the request, and determines an energy-saving strategy according to the comparison of the workload;
the node computing equipment receives the scheduling executed by the cloud computing environment platform according to the energy-saving strategy, then executes the workload, and after the computing processing is finished, transmits the processing result back to the cloud computing environment platform; and
the cloud computing environment platform further sends the result of the cloud computing request to the client.
FIG. 3 illustrates a flow chart of a method for enhancing energy savings in a cloud computing environment, according to an exemplary embodiment of the present invention. Specifically, the method comprises the following steps:
in step S1, receiving a cloud computing request sent from a client;
in step S2, the cloud computing environment platform performs security authentication on the computing request, and executes step S3 after the authentication is passed;
in step S3, the cloud computing environment platform analyzes, evaluates, and obtains the workload included in the request;
in step S4, the cloud computing environment platform determines whether the cloud computing request has been previously requested to be processed by invoking the history database analysis, and if so, directly invokes the previous processing result from the history database, and performs step S10; if not previously processed, go to step S5;
in step S5, the cloud computing environment platform updates the capability, capacity and priority of each node computing device;
in step S6, the cloud computing environment platform compares the workload included in the request with the information processing margin in the existing node computing device one by one according to the priority of the existing node computing device;
in step S7, if the former is smaller than the latter, the workload included in the request is encrypted according to the priority and delivered to the selected node computing device, and after the computing process is finished, the workload is delivered back to the cloud computing environment platform; then step S9 is executed;
in step S8, if the former is greater than the latter, the configuration of the host and the virtual machine in the node computing device and/or the migration and/or combination of the virtual machine are performed to reduce the total number of the node computing devices used, and the workload included in the request is encrypted and delivered to the selected node computing device, and after the computing process is finished, the workload is delivered back to the cloud computing environment platform; then step S9 is executed;
in step S9, the cloud computing environment platform decrypts the data;
in step S10, the cloud computing environment platform sends the result of the computing-processed cloud computing request to the client.
Accordingly, the cloud computing environment C in the enhanced cloud computing environment energy saving system further comprises a history database, and the cloud computing environment C is configured to:
receiving, by the cloud computing environment platform, a cloud computing request sent from a client;
the cloud computing environment platform carries out security authentication on the computing request, and the following operations are executed after the authentication is passed;
analyzing, evaluating and acquiring the workload included in the request by the cloud computing environment platform;
the cloud computing environment platform analyzes and judges whether the cloud computing request is requested to be processed or not by calling the historical database, if the cloud computing request is processed, the cloud computing environment platform directly calls a previous processing result from the historical database and sends a cloud computing request result subjected to computing processing to the client; if not previously processed, continue;
updating the capacity, the capacity and the priority of each node computing device by the cloud computing environment platform;
comparing, by the cloud computing environment platform, the workload included in the request with the information processing margin in the existing node computing device one by one, according to the priority of the existing node computing device;
if the former is smaller than the latter, the cloud computing environment platform encrypts the workload included in the request according to the priority and then delivers the encrypted workload to the selected node computing equipment, and after the computing processing is finished, the encrypted workload is delivered back to the cloud computing environment platform; then, the following decryption is performed;
if the former is larger than the latter, the cloud computing environment platform configures the host and the virtual machine in the node computing equipment and/or migrates and/or combines the virtual machine to reduce the total number of the used node computing equipment, encrypts the workload included in the request and delivers the encrypted workload to the selected node computing equipment, and after the computing processing is finished, delivers the encrypted workload to the cloud computing environment platform; then, the following decryption is performed;
decrypting, by the cloud computing environment platform, the data;
and sending the result of the cloud computing request subjected to computing processing to the client by the cloud computing environment platform.
Specifically, the client may be a user, a desktop or portable PC, a terminal with a PC function, a mobile device such as a mobile phone or a mobile phone, or a user equipment UE in communication technology.
Specifically, the cloud computing environment platform first identifies the information type in the request, removes the request header information therein, and retains, evaluates and acquires the to-be-processed information included in the request, that is, the workload of the to-be-computed processing.
Specifically, the priority of the existing node computing device is determined based on the performance and capacity of the central processor, the static memory and the dynamic memory of the node computing device, and the parameters are updated to the cloud computing environment platform periodically.
The information processing margin in the existing node computing device is the preset threshold of the existing node computing device minus the workload at the current time point, where the preset threshold is the total performance and capacity of the node computing device multiplied by a certain proportion, such as 80%, to ensure normal operation without causing the node computing device to run at full capacity or exceed the operational capacity or causing the node computing device to have a reduced life span due to long-term high utilization.
In addition, the node computing device includes, but is not limited to, a host including a virtual machine, and may further include other information processing devices located at the node, such as a scheduling computing device.
FIG. 4 illustrates a flow diagram of a process for configuring and/or migrating and/or combining virtual machines in a node computing device to reduce the total number of node computing devices used and computing processes, according to an exemplary embodiment of the present invention;
specifically, in step S5, the configuration of the host and the virtual machine in the node computing device and/or the migration and/or combination of the virtual machine are performed to reduce the total number of the node computing devices used, and the calculation processing includes:
in step S510, identifying a virtual machine to be migrated;
in step S511, the use parameter Par of the central processor of the host i to be tested to be migrated is obtainediThe parameter PariThe sum is the quadratic sum of the difference between the currently processed workload of the central processor of host i and the host distribution mean, and then the quotient of the sum and the number of hosts, i.e.:
where represents the current processing workload of the central processor of host i, B represents the host distribution average, and M represents the number of hosts, which is a positive integer having a value of at least 2.
In step S512, step S511 is repeated for the same virtual machine to be migrated until M hosts.
In step S513, for the jth virtual machine to be migrated, steps S511-S512 are repeated until M hosts execute until N virtual machines to be migrated, that is, execute M × (N-1) times, where N represents the number of virtual machines to be migrated and has a positive integer value of at least 2.
In step S514, for each virtual machine to be migrated and each host, an array Ary of use parameters of the central processor is created:
in step S515, a minimum value is selected from each row, and a minimum value array Ary of use parameters of the central processor is createdMIN，
In step S516, Ary is calculatedMINCorresponding to the preferred migratable virtual machine and the preferred host machine.
Accordingly, the node computing device in the enhanced cloud computing environment energy-saving system is configured to:
in the case where the amount of work included in the request is greater than the information processing margin in the existing node computing device,
identifying a virtual machine to be migrated;
obtaining the use parameters Par of the central processing unit of the host i to be tested to be migratediThe parameter PariThe sum is the quadratic sum of the difference between the currently processed workload of the central processor of host i and the host distribution mean, and then the quotient of the sum and the number of hosts, i.e.:
where represents the current processing workload of the central processor of host i, B represents the host distribution average, and M represents the number of hosts, which is a positive integer having a value of at least 2.
And repeating the previous operation for the same virtual machine to be migrated until M hosts.
And for the jth virtual machine to be migrated, repeating the previous two steps until M hosts, and repeating the execution until N virtual machines to be migrated, namely executing M (N-1) times, wherein N represents the number of the virtual machines to be migrated, and the value of N is a positive integer of at least 2.
For each virtual machine to be migrated and each host, an array Ary of central processor usage parameters is created:
selecting the minimum from each row, creating an array of minima of use parameters Ary of the central processorMIN，
Computing AryMINCorresponding to the preferred migratable virtual machine and the preferred host, and performs a scheduled allocation migration.
Fig. 5 illustrates an alternative flow diagram for performing configuration of hosts and virtual machines in a node computing device and/or migration and/or combination of virtual machines to reduce the total number of node computing devices used and to compute processes, according to an exemplary embodiment of the present invention.
Alternatively, step S5 includes the steps of:
in step S520, the number of virtual machines of the unit processing capacity to be scheduled is calculated according to the workload included in the request;
in step S521, the plurality of virtual machines of the unit processing capacity to be scheduled are decomposed into groups;
in step S522, it is determined whether the virtual machine needs to be migrated according to the number of packets; if the critical value is exceeded, the requirement is needed, otherwise, the requirement is not needed;
in step S523, if there are enough node computing devices in the low power consumption state, migrating the virtual machine in the previous step to the node computing device in the low power consumption state according to the performance and capacity of the central processing unit, the static memory, and the dynamic memory of the node computing device in the low power consumption state; if the data is insufficient, according to the performances and capacities of a central processing unit, a static memory and a dynamic memory of the node computing equipment in the low power consumption state, the signing performance and capacity are divided by the unit processing capacity, and data of an integer number of unit processing capacity are transmitted to the node computing equipment in the low power consumption state by adopting a rounding and tailing removing method;
where low power states include, but are not limited to, sleep, standby, run-to-delay waiting (in order to optimize power consumption and to take into account boot rate and processing efficiency, delays are often used in the art from run-to-sleep or standby to respond quickly when needed).
Accordingly, the node computing device in the enhanced cloud computing environment energy-saving system is configured to:
in the case where the amount of work included in the request is greater than the information processing margin in the existing node computing device,
calculating the number of virtual machines with unit processing capacity to be scheduled according to the workload included in the request;
decomposing a plurality of virtual machines of unit processing capacity to be scheduled into groups;
determining whether the virtual machine needs to be migrated according to the number of the packets; if the critical value is exceeded, the requirement is needed, otherwise, the requirement is not needed;
if the node computing equipment in the low power consumption state is enough, migrating the virtual machine in the previous step to the node computing equipment in the low power consumption state according to the performances and capacities of a central processing unit, a static memory and a dynamic memory of the node computing equipment in the low power consumption state; if the data is insufficient, according to the performances and capacities of a central processing unit, a static memory and a dynamic memory of the node computing equipment in the low power consumption state, the signing performance and capacity are divided by the unit processing capacity, and data of an integer number of unit processing capacity are transmitted to the node computing equipment in the low power consumption state by adopting a rounding and tailing removing method; wherein the low power states include, but are not limited to, sleep, standby, running into delayed waiting.
Calculating the number of virtual machines of the unit processing capacity to be scheduled according to the workload included in the request further comprises: the number is obtained in the following manner
Wherein DkRepresenting the number of virtual machines, EkA numerical value indicating the amount of tasks of the virtual machine, E the number of servers, and L.
In addition, particularly, the cloud computing environment platform encrypts and decrypts data, so that potential safety hazards in data computing processing due to the fact that a plurality of node computing devices are connected in the cloud computing environment can be eliminated.
Fig. 6 illustrates an energy saving effect diagram of the present invention with respect to the prior art, according to an exemplary embodiment of the present invention. Wherein: item A represents the method and system adopted by the invention, item B represents the method and system for scheduling load by giving priority to queuing or sequencing in the prior art; the horizontal axis represents the request rate issued by the client in units of the order of ten per minute and the vertical axis represents the power saving ratio. Through tests, compared with the method and the system adopted by the prior art, the method and the system have 1% -4% improvement, and have great improvement on energy saving effect for a large cloud computing environment.
In summary, in the technical solution of the present invention, the system for enhancing energy saving in cloud computing environment described herein includes: the client sends a cloud computing request and is received by the cloud computing environment platform; the cloud computing environment platform analyzes, evaluates and obtains the workload included in the request, and determines an energy-saving strategy according to the comparison of the workload; the node computing equipment receives scheduling executed by the cloud computing environment platform according to the energy-saving strategy, then executes the workload, and after computing processing is finished, transmits a processing result back to the cloud computing environment platform; and the cloud computing environment platform further sends the result of the cloud computing request to the client. The system can effectively reduce energy consumption of node processing equipment such as physical computing equipment, virtual computing equipment and the like in the cloud computing environment, further improve the efficiency of scheduling, migration and combination of the virtual machines, and enhance the safety of the cloud computing environment.
It will be understood that: the examples and embodiments of the invention may be implemented in hardware, software, or a combination of hardware and software. As mentioned above, any body performing such a method may be stored in the form of volatile or non-volatile storage, for example a storage device like a ROM, whether erasable or rewritable or not, or in the form of memory, such as for example a RAM, a memory chip, a device or an integrated circuit or on an optically or magnetically readable medium such as for example a CD, a DVD, a disk or a tape. It will be understood that: storage devices and storage media are examples of machine-readable storage suitable for storing one or more programs that, when executed, implement examples of the present invention. Examples of the present invention may be conveyed electronically via any medium, such as a communication signal carried over a wired or wireless connection, and the examples contain the same where appropriate.
It should be noted that: since the present invention adopts the technical means that can be understood by those skilled in the computer field according to the teachings of the present specification after reading the present specification, the present invention solves the technical problems and obtains the technical effects of effectively reducing the energy consumption of the node processing devices such as the physical computing devices and the virtual computing devices in the cloud computing environment, further improving the efficiency of scheduling, migrating, and merging the virtual machines, and enhancing the security of the cloud computing environment, the solution claimed in the appended claims belongs to the technical solution in the meaning of patent law. Furthermore, the solution claimed in the appended claims has utility since it can be manufactured or used in industry.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Unless expressly stated otherwise, each feature disclosed is one example only of a generic series of equivalent or similar features. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. An enhanced cloud computing environment energy saving system, comprising:
the client sends a cloud computing request and is received by the cloud computing environment platform; and
a cloud computing environment C comprising a cloud computing environment platform and a node computing device, wherein:
the cloud computing environment platform analyzes, evaluates and obtains the workload included in the request, and determines an energy-saving strategy according to the comparison of the workload;
the node computing equipment is used for executing scheduling according to the energy-saving strategy received from the cloud computing environment platform and then executing the workload, and after the computing processing is finished, the processing result is delivered back to the cloud computing environment platform; and
the cloud computing environment platform further sends a result of the cloud computing request to the client;
wherein the cloud computing environment C in the enhanced cloud computing environment energy-saving system further comprises:
a history database, and
the cloud computing environment C is configured to:
receiving, by the cloud computing environment platform, a cloud computing request sent from a client;
the cloud computing environment platform carries out security authentication on the cloud computing request, and the following operations are executed after the authentication is passed;
analyzing, evaluating and acquiring the workload included in the request by the cloud computing environment platform;
the cloud computing environment platform analyzes and judges whether the cloud computing request is requested to be processed or not by calling the historical database, if the cloud computing request is processed, the cloud computing environment platform directly calls a previous processing result from the historical database and sends a cloud computing request result subjected to computing processing to the client; if not previously processed, continue;
updating the capacity, the capacity and the priority of each node computing device by the cloud computing environment platform;
comparing, by the cloud computing environment platform, the workload included in the request with the information processing margin in the existing node computing device one by one, according to the priority of the existing node computing device;
if the former is smaller than the latter, the cloud computing environment platform encrypts the workload included in the request according to the priority and then delivers the encrypted workload to the selected node computing equipment, and after the computing processing is finished, the encrypted workload is delivered back to the cloud computing environment platform; then, the following decryption is performed;
if the former is larger than the latter, the cloud computing environment platform configures the host and the virtual machine in the node computing equipment and/or migrates and/or combines the virtual machine to reduce the total number of the used node computing equipment, encrypts the workload included in the request and delivers the encrypted workload to the selected node computing equipment, and after the computing processing is finished, delivers the encrypted workload to the cloud computing environment platform; then, the following decryption is performed;
decrypting, by the cloud computing environment platform, the data;
sending, by the cloud computing environment platform, a result of the computing-processed cloud computing request to the client;
wherein: the node computing device in the enhanced cloud computing environment energy-saving system is configured to:
in the case where the amount of work included in the request is greater than the information processing margin in the existing node computing device,
identifying a virtual machine to be migrated;
obtaining the use parameters Par of the central processing unit of the host i to be tested to be migratediThe parameter PariThe sum is the quadratic sum of the difference between the currently processed workload of the central processor of this host i and the host distribution mean, and then the quotient of the number of hosts, i.e.:
wherein A isiRepresenting the current processing workload of the central processor of host i, B representing the host distribution mean, and M representing the number of hosts, which is a positive integer having a value of at least 2；
Repeating the previous operation for the same virtual machine to be migrated until M hosts;
for the jth virtual machine to be migrated, repeating the previous two steps until M hosts, and repeating the execution until N virtual machines to be migrated, namely executing M (N-1) times, wherein N represents the number of the virtual machines to be migrated, and the value of N is a positive integer of at least 2;
for each virtual machine to be migrated and each host, an array Ary of central processor usage parameters is created:
selecting the minimum from each row, creating an array of minima of use parameters Ary of the central processorMIN，
Computing AryMINCorresponding to the preferred migratable virtual machine and the preferred host, and performs a scheduled allocation migration.
2. The enhanced cloud computing environment energy-saving system of claim 1, wherein:
the node computing device in the enhanced cloud computing environment energy-saving system is configured to:
in the case where the amount of work included in the request is greater than the information processing margin in the existing node computing device,
calculating the number of virtual machines with unit processing capacity to be scheduled according to the workload included in the request;
decomposing a plurality of virtual machines of unit processing capacity to be scheduled into groups;
determining whether the virtual machine needs to be migrated according to the number of the packets; if the critical value is exceeded, the requirement is needed, otherwise, the requirement is not needed;
if the node computing equipment in the low power consumption state is enough, migrating the virtual machine in the previous step to the node computing equipment in the low power consumption state according to the performances and capacities of a central processing unit, a static memory and a dynamic memory of the node computing equipment in the low power consumption state; if the data is insufficient, according to the performances and capacities of a central processing unit, a static memory and a dynamic memory of the node computing equipment in the low power consumption state, the signing performance and capacity are divided by the unit processing capacity, and data of an integral number of unit processing capacities are transmitted to the node computing equipment in the low power consumption state by adopting a rounding and tailing removing method.
3. The enhanced cloud computing environment energy saving system of claim 2, wherein the low power consumption state comprises a state of sleep, standby, running to delayed wait.
4. The enhanced cloud computing environment energy saving system of claim 2 or 3, wherein calculating the number of virtual machines of a unit processing capacity to be scheduled according to the workload included in the request further comprises: the number is obtained in the following manner
Wherein DkRepresenting the number of virtual machines, EkA numerical value representing the amount of tasks of the virtual machine, and E representing the number of servers.
5. The enhanced cloud computing environment energy saving system of claim 4, wherein the information handling margin in the existing node computing devices is a preset threshold of the existing node computing devices minus the amount of work at the current point in time, the preset threshold being a ratio of the total performance and capacity of the node computing devices multiplied by at least 80%.
6. The enhanced cloud computing environment energy saving system of claim 4, the client comprising any one of: a user, a desktop or laptop PC, a terminal with PC functionality or a user equipment UE in communication technology.
7. The enhanced cloud computing environment energy saving system of claim 4, wherein the priority of the existing node computing devices is determined based on the performance and capacity of the central processor, static memory, dynamic memory of the node computing devices, and these parameters are updated to the cloud computing environment platform periodically.
8. The enhanced cloud computing environment energy-saving system of claim 4, wherein
The cloud computing environment platform firstly identifies the information type in the request, removes the request header information in the request, and reserves, evaluates and acquires the information to be processed, namely the workload of the to-be-computed processing, included in the request.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710357258.0A CN107197013B (en) | 2017-05-19 | 2017-05-19 | Energy-saving system for enhancing cloud computing environment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710357258.0A CN107197013B (en) | 2017-05-19 | 2017-05-19 | Energy-saving system for enhancing cloud computing environment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107197013A CN107197013A (en) | 2017-09-22 |
| CN107197013B true CN107197013B (en) | 2020-03-20 |
Family
ID=59875180
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710357258.0A Active CN107197013B (en) | 2017-05-19 | 2017-05-19 | Energy-saving system for enhancing cloud computing environment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107197013B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108388473A (en) * | 2018-02-01 | 2018-08-10 | 广东聚晨知识产权代理有限公司 | A kind of computing system of big data |
| CN110149341B (en) * | 2019-05-29 | 2020-06-16 | 燕山大学 | Cloud system user access control method based on sleep mode |
| CN110543363A (en) * | 2019-08-05 | 2019-12-06 | 慧镕电子系统工程股份有限公司 | Virtual machine management method in cloud computing environment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102073462A (en) * | 2010-11-29 | 2011-05-25 | 华为技术有限公司 | Virtual storage migration method and system and virtual machine monitor |
| CN103823718A (en) * | 2014-02-24 | 2014-05-28 | 南京邮电大学 | Resource allocation method oriented to green cloud computing |
| CN104657215A (en) * | 2013-11-19 | 2015-05-27 | 南京鼎盟科技有限公司 | Virtualization energy-saving system in Cloud computing |
| CN106126344A (en) * | 2016-06-30 | 2016-11-16 | 中国联合网络通信集团有限公司 | A kind of method for allocating tasks and device |
-
2017
- 2017-05-19 CN CN201710357258.0A patent/CN107197013B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102073462A (en) * | 2010-11-29 | 2011-05-25 | 华为技术有限公司 | Virtual storage migration method and system and virtual machine monitor |
| CN104657215A (en) * | 2013-11-19 | 2015-05-27 | 南京鼎盟科技有限公司 | Virtualization energy-saving system in Cloud computing |
| CN103823718A (en) * | 2014-02-24 | 2014-05-28 | 南京邮电大学 | Resource allocation method oriented to green cloud computing |
| CN106126344A (en) * | 2016-06-30 | 2016-11-16 | 中国联合网络通信集团有限公司 | A kind of method for allocating tasks and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107197013A (en) | 2017-09-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zhou et al. | Minimizing SLA violation and power consumption in Cloud data centers using adaptive energy-aware algorithms | |
| Zhou et al. | Virtual machine placement algorithm for both energy‐awareness and SLA violation reduction in cloud data centers | |
| US8402140B2 (en) | Methods and apparatus for coordinated energy management in virtualized data centers | |
| US8635625B2 (en) | Power-aware workload allocation in performance-managed computing environments | |
| CN102508718A (en) | Method and device for balancing load of virtual machine | |
| Liu et al. | A survey on virtual machine scheduling in cloud computing | |
| CN103037109B (en) | Multicore equipment energy consumption management method and device | |
| CN107197013B (en) | Energy-saving system for enhancing cloud computing environment | |
| Sharma et al. | Novel energy efficient virtual machine allocation at data center using Genetic algorithm | |
| Zhang et al. | An Energy and SLA‐Aware Resource Management Strategy in Cloud Data Centers | |
| Choi et al. | Task Classification Based Energy‐Aware Consolidation in Clouds | |
| Panda et al. | An efficient energy saving task consolidation algorithm for cloud computing systems | |
| Rahmani et al. | Burst‐aware virtual machine migration for improving performance in the cloud | |
| CN110830560A (en) | Multi-user mobile edge calculation migration method based on reinforcement learning | |
| Zhang et al. | A new energy efficient VM scheduling algorithm for cloud computing based on dynamic programming | |
| CN103488538A (en) | Application extension device and application extension method in cloud computing system | |
| Samadi et al. | DT-MG: Many-to-one matching game for tasks scheduling towards resources optimization in cloud computing | |
| Chen et al. | Utilization-based VM consolidation scheme for power efficiency in cloud data centers | |
| CN104468710A (en) | Mixed big data processing system and method | |
| CN106802822A (en) | A kind of cloud data center cognitive resources dispatching method based on moth algorithm | |
| CN107193362B (en) | Energy-saving device for enhancing cloud computing environment | |
| CN108073449B (en) | Dynamic virtual machine placement method | |
| CN107154979B (en) | Energy-saving method for enhancing cloud computing environment | |
| Singh et al. | A green computing supportive allocation scheme utilizing genetic algorithm and support vector machine | |
| Leite et al. | Power‐aware server consolidation for federated clouds |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20200123 Address after: Phase II of Goldman Sachs Science Park, No. 5, zhouxilongxi Road, Nancheng District, Dongguan City, Guangdong Province Applicant after: Dongguan Mengda Plasticizing Technology Co., Ltd. Address before: The middle Tianfu Avenue in Chengdu city Sichuan province 610000 No. 1388 1 7 storey building No. 772 Applicant before: CHENGDU DINGZHIHUI SCIENCE AND TECHNOLOGY CO., LTD. |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP03 | Change of name, title or address |
Address after: 523000 room 1301, unit 2, building 4, Tian'an Digital City, No. 1, Huangjin Road, Nancheng street, Dongguan City, Guangdong Province Patentee after: Dongguan Mengda Group Co.,Ltd. Address before: 523000 Goldman Sachs science and Technology University, phase II, Goldman Sachs science and Technology Park, No. 5, Longxi Road, Zhouxi, Nancheng District, Dongguan City, Guangdong Province Patentee before: DONGGUAN MENGDA PLASTICIZING SCIENCE & TECHNOLOGY Co.,Ltd. |
|
| CP03 | Change of name, title or address |