CN107479949A - Low energy consumption cloud computing method for scheduling task - Google Patents
Low energy consumption cloud computing method for scheduling task Download PDFInfo
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- CN107479949A CN107479949A CN201710720291.5A CN201710720291A CN107479949A CN 107479949 A CN107479949 A CN 107479949A CN 201710720291 A CN201710720291 A CN 201710720291A CN 107479949 A CN107479949 A CN 107479949A
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- 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
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
-
- 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
- G06F9/48—Program initiating; Program switching, e.g. by interrupt
- G06F9/4806—Task transfer initiation or dispatching
- G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
- G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
-
- 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
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
- G06F2009/45562—Creating, deleting, cloning virtual machine instances
-
- 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
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
- G06F2009/4557—Distribution of virtual machine instances; Migration and load balancing
-
- 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
Abstract
The invention discloses low energy consumption cloud computing method for scheduling task, comprise the following steps：Step 1）The task that user submits is received, the task list that need to currently dispatch is obtained, if receiving user task first, then performs next step；Otherwise, step 3 is turned to）；Step 2）System initialization, virtual machine is created according to number of tasks, virtual machine number is twice of the number of tasks that user submits, obtains virtual machine list, while the parameter of each virtual machine is initialized；Step 3）Judge whether task list is empty, if it is, destroying virtual machine, overall process terminates；Otherwise, next step is performed；Step 4）According to least energy consumption strategy, task scheduling is performed to the minimum virtual machine of energy consumption.Operation cost with reduction data center, reduce the technique effect of energy resource consumption.
Description
Technical field
The present invention relates to field of cloud computer technology, and in particular to a kind of low energy consumption cloud computing method for scheduling task.
Background technology
Cloud computing system has provided the user substantial amounts of calculating and storage resource, is current business and scientific research institution both at home and abroad
One of focus of research, calculating task is distributed in the resource pool of a large amount of computers compositions by it（Such as data center）On, make various
Application system can obtain computing power, memory space and information service on demand.
Cloud computing relies on data center, using virtualization technology by the resource impact of main frame to virtual machine layer, execution user
Task.Virtualization technology (such as VMware, Xen and Microsoft Virtual Servers) by flexible resource management,
The technologies such as online migration, a feasible path is provided efficiently to manage the server resource of data center.These virtualizations
Technology allows to generate more virtual machines (Virtual Machine, VM) on a physical server, can on every VM
To run different operating system and application, while all VM share the hardware resource of bottom, and server money is improved to reach
The purpose of source utilization rate, therefore cloud computing server is built in current data center using virtualization technology one after another.With virtual
The application of change technology, effective task scheduling technique for improve cloud computing efficiency become particularly important, task scheduling be by
Task is mapped with resource using certain optimization aim as principle.Passing task scheduling technique, often to meet user
The QoS requirement specified, and reduce when performing user task for the purpose of usage time, but as the IT equipment in cloud is got over
Come more, scale is increasing, and energy consumption cost problem is also more and more obvious, the as shown by data from Environmental Protection Agency, currently
Cloud computation data center have become one of carbon emission amount source that can not be ignored in world wide；Therefore, design is efficiently closed
The low energy consumption cloud computing method for scheduling task of reason is to reducing the operation cost of data center and reducing energy resource consumption to environment
Pollution all tools are of great significance.
The content of the invention
The invention is intended to provide a kind of low energy consumption cloud computing method for scheduling task, with reduce the operation cost of data center with
And reduce pollution of the energy resource consumption to environment.
Low energy consumption cloud computing method for scheduling task in this programme, comprises the following steps：
Step 1）The task that user submits is received, and the task of arrival is ranked up according to the priority of task, is obtained current
The task list that need to be dispatched, if receiving user task first, then perform next step；Otherwise, step 3 is turned to）；
Step 2）System initialization, virtual machine being created according to number of tasks, virtual machine number is twice of the number of tasks that user submits,
Virtual machine list is obtained, while the parameter of each virtual machine is initialized, parameter includes virtual machine numbering, central processing unit
Quantity, storage allocation size, bandwidth, power, processing speed and state, the original state of virtual machine is available；
Step 3）Judge whether task list is empty, if it is, destroying virtual machine, overall process terminates；Otherwise, next step is performed
Suddenly；
Step 4）According to least energy consumption strategy, task scheduling is performed to the minimum virtual machine of energy consumption.
Method for scheduling task in the present invention is simple, and using least energy consumption as regulation goal, each task selects to make it disappear
The minimum virtual machine of consumption energy consumption is matched, and may ultimately reach total energy consumption minimum.Meanwhile virtual machine is created with twice of quantity,
More possibilities have not only been provided a system to, have added the possibility for the virtual machine for selecting smaller energy consumption；And it is marked off
More than the resource of needs, system total resources will not be fully used during ensureing each virtual machines performing tasks, keep certain
Amount of redundancy；Because system particularly CPU power consumption is not with workload linear rise, and then when CPU is delivered at full capacity
Power consumption can greatly improve, and keep amount of redundancy then to reduce the generation of this case, reduce average total power consumption, reached reduction number
According to the effect of pollution of the operation cost and reduction energy resource consumption at center to environment.
Further, in addition to step 5）Judge whether the clock cycle expires, if it is, performing next step；Otherwise, turn
To step 1）；
Step 6）According to load on host computers, operation plan is adjusted, turns to step 1）.
Increase the clock cycle as one of Rule of judgment, system keeps stablizing constant, periodicity prison within some period
Load on host computers is controlled, adjusts operation plan in time, reaches the balanced effect of energy load.
Further, the step 4）According to least energy consumption strategy, selection task corresponds to the minimum virtual machine of energy consumption and adjusted
Degree comprises the following steps：
Step 401）Represent m task in task list on n virtual machine of establishment with m × n power consuming matrix
The energy consumption of consumption, every a line in matrix represent energy consumption of the same task on n virtual machine, and each row represent m task
Energy consumption on same virtual machine；
Step 402）In power consuming matrix, power consumption values of more each task on each available virtual machine, least energy consumption is taken
Virtual machine and labeled as the virtual machine for performing the task, after completing the observable index of all tasks relatively, obtains the minimum of all tasks
The list of the virtual machine of energy consumption；
Step 403）According to step 402）The list of the virtual machine of the least energy consumption of middle formation, it will appoint successively by task list order
Business is distributed on the virtual machine of corresponding least energy consumption, is often distributed a task, is then deleted the task from task list, directly
To distributing task all in task list.
By comparing one by one, it can simply be judged, simplify algorithm, improve efficiency.
Further, in power consuming matrix, the energy consumption of each task is multiplied by by execution time of the task on some virtual machine
The power consumption of the virtual machine obtains；The execution time is obtained as total instruction number contained by the task divided by the processing speed of the virtual machine
Arrive.
Total instruction number of task is relatively stable, establishes and can estimate well from task, and the processing of virtual machine is fast
Degree is also relatively stable, so being calculated according to such method, power consumption efficiency is high, error is small.
Further, the step 6）According to load on host computers, adjustment operation plan comprises the following steps：
The power consumption utilization rate at the current time of each main frame is calculated, power consumption utilization rate is current power consumption divided by the total power consumption of main frame；
When the power consumption utilization rate of some main frame is less than sleep threshold, dormancy main frame in this clock cycle；
When the power consumption utilization rate of some main frame is higher than saturation threshold, by the main frame labeled as unavailable, the main frame is run on
Power consumption of the virtual machine in power consuming matrix is infinity；
When power consumption utilization rate is higher than overloading threshold higher than the ratio between quantity of the main frame of saturation threshold and main frame sum, dormancy is waken up
Main frame, and virtual machine is created on the main frame of wake-up, the quantity of wake-up master is no more than overload main frame in this clock cycle
Sum.
Brief description of the drawings
Fig. 1 is the indicative flowchart of the embodiment of the present invention.
Embodiment
Below by embodiment, the present invention is further detailed explanation：
The flow of low energy consumption cloud computing method for scheduling task is substantially as shown in Figure 1 in embodiment：
Low energy consumption cloud computing method for scheduling task in this programme, comprises the following steps：
Step 1）The task that user submits is received, and the task of arrival is ranked up according to the priority of task, is obtained current
The task list that need to be dispatched, if receiving user task first, then perform next step；Otherwise, step 3 is turned to）；
Step 2）System initialization, virtual machine being created according to number of tasks, virtual machine number is twice of the number of tasks that user submits,
Virtual machine list is obtained, while the parameter of each virtual machine is initialized, parameter includes virtual machine numbering, central processing unit
Quantity, storage allocation size, bandwidth, power, processing speed and state, the original state of virtual machine is available；
Step 3）Judge whether task list is empty, if it is, destroying virtual machine, overall process terminates；Otherwise, next step is performed
Suddenly；
Step 4）According to least energy consumption strategy, task scheduling is performed to the minimum virtual machine of energy consumption, comprised the following steps：
Step 401）Represent m task in task list on n virtual machine of establishment with m × n power consuming matrix
The energy consumption of consumption, every a line in matrix represent energy consumption of the same task on n virtual machine, and each row represent m task
Energy consumption on same virtual machine；
Step 402）In power consuming matrix, power consumption values of more each task on each available virtual machine, least energy consumption is taken
Virtual machine and labeled as the virtual machine for performing the task, after completing the observable index of all tasks relatively, obtains the minimum of all tasks
The list of the virtual machine of energy consumption；
Step 403）According to step 402）The list of the virtual machine of the least energy consumption of middle formation, it will appoint successively by task list order
Business is distributed on the virtual machine of corresponding least energy consumption, is often distributed a task, is then deleted the task from task list, directly
To distributing task all in task list；
Step 5）Judge whether the clock cycle expires, if it is, performing next step；Otherwise, step 1 is turned to）.
Step 6）According to load on host computers, adjustment operation plan comprises the following steps：
The power consumption utilization rate at the current time of each main frame is calculated, power consumption utilization rate is current power consumption divided by the total power consumption of main frame；
When the power consumption utilization rate of some main frame is less than sleep threshold, dormancy main frame in this clock cycle；
When the power consumption utilization rate of some main frame is higher than saturation threshold, by the main frame labeled as unavailable, the main frame is run on
Power consumption of the virtual machine in power consuming matrix is infinity；
When power consumption utilization rate is higher than overloading threshold higher than the ratio between quantity of the main frame of saturation threshold and main frame sum, dormancy is waken up
Main frame, and virtual machine is created on the main frame of wake-up, the quantity of wake-up master is no more than overload main frame in this clock cycle
Sum;
After adjusting operation plan, then step 1 is turned to）.
In the present embodiment, sleep threshold is preferably 0.1, and saturation threshold is preferably 0.8, and overloading threshold can be selected in
Between 0.7 to 1, the present embodiment has selected 0.8.
In power consuming matrix, the energy consumption of each task is multiplied by the virtual machine by execution time of the task on some virtual machine
Power consumption obtain；The execution time is obtained as total instruction number contained by the task divided by the processing speed of the virtual machine.Task
Total instruction number it is relatively stable, establish and can estimate well from task, and the processing speed of virtual machine is also relatively stable,
So being calculated according to such method, power consumption efficiency is high, error is small.
Method for scheduling task in the present invention is simple, and using least energy consumption as regulation goal, each task selects to make it disappear
The minimum virtual machine of consumption energy consumption is matched, and may ultimately reach total energy consumption minimum, i.e., all tasks carryings, which finish, needs what is consumed
It is minimum to calculate energy consumption.Meanwhile virtual machine is created with twice of quantity, and mark off more than the resource needed, it is virtual every time to ensure
System total resources will not be fully used when machine performs task, keep certain amount of redundancy；Due to system particularly CPU work(
Consumption is not with workload linear rise, and then power consumption can greatly improve when CPU is delivered at full capacity, keeps amount of redundancy then to reduce
The generation of this case, reduces average total power consumption, has reached the operation cost for reducing data center and has reduced the energy and disappears
Consume the effect of the pollution to environment.Increase the clock cycle as one of Rule of judgment, system keeps stable within some period
It is constant.Periodicity monitoring host computer loads, and adjusts operation plan in time, reaches the balanced effect of energy load.
Above-described is only embodiments of the invention, and the general knowledge such as known concrete structure and characteristic is not made herein in scheme
Excessive description, technical field that the present invention belongs to is all before one skilled in the art know the applying date or priority date
Ordinary technical knowledge, prior art all in the field can be known, and with using normal experiment hand before the date
The ability of section, one skilled in the art can improve and implement under the enlightenment that the application provides with reference to self-ability
This programme, some typical known features or known method should not implement the application as one skilled in the art
Obstacle.It should be pointed out that for those skilled in the art, without departing from the structure of the invention, it can also make
Go out several modifications and improvements, these should also be considered as protection scope of the present invention, these effects implemented all without the influence present invention
Fruit and practical applicability.The scope of protection required by this application should be based on the content of the claims, the tool in specification
The records such as body embodiment can be used for the content for explaining claim.
Claims (5)
1. low energy consumption cloud computing method for scheduling task, it is characterised in that comprise the following steps：
Step 1）The task that user submits is received, and the task of arrival is ranked up according to the priority of task, is obtained current
The task list that need to be dispatched, if receiving user task first, then perform next step；Otherwise, step 3 is turned to）；
Step 2）System initialization, virtual machine being created according to number of tasks, virtual machine number is twice of the number of tasks that user submits,
Virtual machine list is obtained, while the parameter of each virtual machine is initialized, parameter includes virtual machine numbering, central processing unit
Quantity, storage allocation size, bandwidth, power, processing speed and state, the original state of virtual machine is available；
Step 3）Judge whether task list is empty, if it is, destroying virtual machine, overall process terminates；Otherwise, next step is performed
Suddenly；
Step 4）According to least energy consumption strategy, task scheduling is performed to the minimum virtual machine of energy consumption.
2. low energy consumption cloud computing method for scheduling task according to claim 1, it is characterised in that：Also include step 5）Judge
Whether the clock cycle expires, if it is, performing next step；Otherwise, step 1 is turned to）；
Step 6）According to load on host computers, operation plan is adjusted, turns to step 1）.
3. low energy consumption cloud computing method for scheduling task according to claim 2, it is characterised in that：The step 6）According to master
Machine loads, and adjustment operation plan comprises the following steps：
The power consumption utilization rate at the current time of each main frame is calculated, power consumption utilization rate is current power consumption divided by the total power consumption of main frame；
When the power consumption utilization rate of some main frame is less than sleep threshold, dormancy main frame in this clock cycle；
When the power consumption utilization rate of some main frame is higher than saturation threshold, by the main frame labeled as unavailable, the main frame is run on
Power consumption of the virtual machine in power consuming matrix is infinity；
When power consumption utilization rate is higher than overloading threshold higher than the ratio between quantity of the main frame of saturation threshold and main frame sum, dormancy is waken up
Main frame, and virtual machine is created on the main frame of wake-up, the quantity of wake-up master is no more than overload main frame in this clock cycle
Sum.
4. low energy consumption cloud computing method for scheduling task according to claim 1, it is characterised in that the step 4）According to most
Small energy consumption strategy, selection task, which corresponds to the minimum virtual machine of energy consumption and is scheduled, to be comprised the following steps：
Step 401）Represent m task in task list on n virtual machine of establishment with m × n power consuming matrix
The energy consumption of consumption, every a line in matrix represent energy consumption of the same task on n virtual machine, and each row represent m task
Energy consumption on same virtual machine；
Step 402）In power consuming matrix, power consumption values of more each task on each available virtual machine, least energy consumption is taken
Virtual machine and labeled as the virtual machine for performing the task, after completing the observable index of all tasks relatively, obtains the minimum of all tasks
The list of the virtual machine of energy consumption；
Step 403）According to step 402）The list of the virtual machine of the least energy consumption of middle formation, it will appoint successively by task list order
Business is distributed on the virtual machine of corresponding least energy consumption, is often distributed a task, is then deleted the task from task list, directly
To distributing task all in task list.
5. low energy consumption cloud computing method for scheduling task according to claim 4, it is characterised in that：In the power consuming matrix,
The power consumption that the energy consumption of each task is multiplied by the virtual machine by execution time of the task on some virtual machine obtains；The execution
Time is obtained as total instruction number contained by the task divided by the processing speed of the virtual machine.
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| CN108574600A (en) * | 2018-03-20 | 2018-09-25 | 北京航空航天大学 | The QoS guarantee method of the power consumption and resource contention Collaborative Control of cloud computing server |
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Application publication date: 20171215 |