CN108984273A - A kind of method and device of scheduling virtual machine - Google Patents
A kind of method and device of scheduling virtual machine Download PDFInfo
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- CN108984273A CN108984273A CN201810814517.2A CN201810814517A CN108984273A CN 108984273 A CN108984273 A CN 108984273A CN 201810814517 A CN201810814517 A CN 201810814517A CN 108984273 A CN108984273 A CN 108984273A
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- performance data
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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
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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
- G06F2009/4557—Distribution of virtual machine instances; Migration and load balancing
Abstract
The invention discloses a kind of methods of scheduling virtual machine, comprising: analyzes in real time the performance data of physical machine, predicts the performance data of physical machine described in subsequent time；The performance data of the physical machine subsequent time and the performance data of virtual machine are compared, the maximum physical machine of performance data difference with the virtual machine is obtained；The virtual machine is arranged in acquired physical machine.The invention also discloses a kind of devices of scheduling virtual machine.This programme can carry out dynamic dispatching to virtual machine according to the algorithm policy of setting, improve the harmony and resource utilization of cluster resource by analyzing in real time the performance data of physical machine.
Description
Technical field
The present embodiments relate to cloud computing technology, espespecially a kind of method and device of scheduling virtual machine.
Background technique
Cloud computing is the new design philosophy and network technology formed by the fast development of Web application.Cloud computing technology
Advantage is that, by the way that limited infrastructure is integrated, resource, which is passed through abstract and grain refined and is supplied to user on demand, to be made
With.The appearance of cloud computing technology alleviates the burden of client, as long as user is connected to cloud in any terminal, script to service
The resource request of device is submitted to cloud, and remaining calculating task and result are completed in cloud.The core of cloud computing is dependent on void
Quasi-ization technology, exactly this technology are the flexible Ground Split of cloud resource and integration, while user can be made with the smallest cost and cost
Use cloud platform.Scheduling of resource is the important channel that system improves resource utilization, the key of the scheduling research based on virtual machine
First is that the Placement of virtual machine, traditional algorithm randomly placed can cause virtual machine frequently to migrate, each dimension of cluster
Resource service condition it is also irregular.
Summary of the invention
In order to solve the above-mentioned technical problems, the present invention provides a kind of methods of scheduling virtual machine, unnecessary to reduce
The migration bring computing cost of virtual machine and the wasting of resources improve the harmony and resource utilization of cluster resource.
In order to reach the object of the invention, the present invention provides a kind of methods of scheduling virtual machine, comprising:
The performance data of physical machine is analyzed in real time, predicts the performance data of physical machine described in subsequent time；
The performance data of the physical machine subsequent time and the performance data of virtual machine are compared, is obtained and the virtual machine
The maximum physical machine of performance data difference；
The virtual machine is arranged in acquired physical machine.
Optionally, it is described in real time to the performance data of physical machine carry out analysis be achieved in the following ways:
Time sequence analysis algorithm.
Optionally, the performance data of physical machine described in the prediction subsequent time, comprising:
Predict the service condition of the resource of each dimension of physical machine described in subsequent time.
Optionally, the performance data for comparing the physical machine subsequent time and the performance data of virtual machine be by with
What under type was realized:
Utilize the clustering algorithm for maximizing difference in class.
A kind of device of scheduling virtual machine, wherein include:
Analysis module predicts physical machine described in subsequent time for analyzing in real time the performance data of physical machine
Performance data；
Module is obtained, for comparing the performance data of the physical machine subsequent time and the performance data of virtual machine, is obtained
With the maximum physical machine of performance data difference of the virtual machine；
Module is arranged, for the virtual machine to be arranged in acquired physical machine.
Further, the analysis module, it is real in the following manner for carrying out analysis to the performance data of physical machine in real time
Existing: time sequence analysis algorithm.
Further, the analysis module predicts the performance data of physical machine described in subsequent time, comprising: prediction is next
The service condition of the resource of each dimension of physical machine described in moment.
Further, the acquisition module compares the performance data of the physical machine subsequent time and the performance of virtual machine
Data are achieved in the following ways: utilizing the clustering algorithm for maximizing difference in class.
A kind of device of scheduling virtual machine, including processor and computer readable storage medium, it is described computer-readable to deposit
Instruction is stored in storage media, wherein when described instruction is executed by the processor, realize the side of above-mentioned scheduling virtual machine
Method.
The scheme of the embodiment of the present invention, by collecting the performance data of physical machine, with time series algorithm to physical machine
The performance of subsequent time predicted.With improved clustering algorithm, virtual machine is placed on its performance data difference most
In big physical machine, to reduce migration bring computing cost and the wasting of resources of unnecessary virtual machine, cluster resource is improved
Harmony and resource utilization.
The other feature and advantage of invention will illustrate in the following description, also, partly become from specification
It is clear that understand through the implementation of the invention.The objectives and other advantages of the invention can be by wanting in specification, right
Specifically noted structure is sought in book and attached drawing to be achieved and obtained.
Detailed description of the invention
Attached drawing is used to provide to further understand technical solution of the present invention, and constitutes part of specification, with this
The embodiment of application technical solution for explaining the present invention together, does not constitute the limitation to technical solution of the present invention.
Fig. 1 is a kind of flow chart of the method for scheduling virtual machine of the embodiment of the present invention；
Fig. 2 is a kind of schematic diagram of the device of scheduling virtual machine of the embodiment of the present invention.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with attached drawing to the present invention
Embodiment be described in detail.It should be noted that in the absence of conflict, in the embodiment and embodiment in the application
Feature can mutual any combination.
Step shown in the flowchart of the accompanying drawings can be in a computer system such as a set of computer executable instructions
It executes.Also, although logical order is shown in flow charts, and it in some cases, can be to be different from herein suitable
Sequence executes shown or described step.
Fig. 1 is a kind of flow chart of the method for scheduling virtual machine of the embodiment of the present invention, as shown in Figure 1, the present embodiment
Method may include:
Step 101 in real time analyzes the performance data of physical machine, predicts the performance number of physical machine described in subsequent time
According to；
The performance data of step 102, the performance data for comparing the physical machine subsequent time and virtual machine, obtain with it is described
The maximum physical machine of performance data difference of virtual machine；
The virtual machine is arranged in acquired physical machine by step 103.
The method of the present embodiment is by real time analyzing the performance data of physical machine, according to the algorithm policy pair of setting
Virtual machine carries out dynamic dispatching, improves the harmony and resource utilization of cluster resource.
It can be realized using time sequence analysis algorithm in the present embodiment and the performance data of physical machine is divided in real time
Analysis carries out dynamic management to virtual machine to realize.
Since the performance of physical machine is constantly to change at any time, the use feelings of the resource of the different dimensions of physical machine
Condition is not also identical, therefore, can be with each dimension of time sequence analysis algorithm prediction subsequent time physical machine in the present embodiment
The service condition of the resource of degree.
In one embodiment, the performance of the physical machine subsequent time is compared using the clustering algorithm for maximizing difference in class
The performance data of data and virtual machine obtains the maximum physical machine of performance data difference with the virtual machine, will be described virtual
Machine is arranged in acquired physical machine, avoids the frequent migration of virtual machine, improves the load balancing of resource utilization and cluster
Property.
For example, it is directed to CPU core number, the memory size of virtual machine and physical machine, the performance data of disk size etc., by poly-
Class algorithm, which acquires, maximizes difference in class, then is exactly that the virtual machine is optimal with the maximum physical machine of virtual machine performance data difference
Deployed position.
The method of the embodiment of the present invention, by collecting the performance data of physical machine, with time series algorithm to physical machine
The performance of subsequent time predicted.With improved clustering algorithm, virtual machine is placed on its performance data difference most
In big physical machine, to reduce migration bring computing cost and the wasting of resources of unnecessary virtual machine, cluster resource is improved
Harmony and resource utilization.
Fig. 2 is a kind of schematic diagram of the device of scheduling virtual machine of the embodiment of the present invention, as shown in Fig. 2, the present embodiment
Device 200 may include:
Analysis module 201 predicts physical machine described in subsequent time for analyzing in real time the performance data of physical machine
Performance data；
Module 202 is obtained to obtain for comparing the performance data of the physical machine subsequent time and the performance data of virtual machine
Take the maximum physical machine of performance data difference with the virtual machine；
Module 203 is arranged, for the virtual machine to be arranged in acquired physical machine.
The device of the present embodiment is by real time analyzing the performance data of physical machine, according to the algorithm policy pair of setting
Virtual machine carries out dynamic dispatching, improves the harmony and resource utilization of cluster resource.
In one embodiment, analysis module 201, analyzing in real time the performance data of physical machine can be by with lower section
What formula was realized: time sequence analysis algorithm carries out dynamic management to virtual machine to realize.
In one embodiment, analysis module 201 predict the performance data of physical machine described in subsequent time, may include: pre-
Survey the service condition of the resource of each dimension of physical machine described in subsequent time.
Since the performance of physical machine is constantly to change at any time, the use feelings of the resource of the different dimensions of physical machine
Condition is not also identical, therefore, can be with each dimension of time sequence analysis algorithm prediction subsequent time physical machine in the present embodiment
The service condition of the resource of degree.
In one embodiment, module 202 is obtained, the performance data of the physical machine subsequent time and the property of virtual machine are compared
Energy data can be accomplished by the following way: utilize the clustering algorithm for maximizing difference in class.
The present embodiment compares the performance data of the physical machine subsequent time using the clustering algorithm for maximizing difference in class
With the performance data of virtual machine, the maximum physical machine of performance data difference with the virtual machine is obtained, by the virtual machine cloth
It sets in acquired physical machine, avoids the frequent migration of virtual machine, improve the load equilibrium of resource utilization and cluster.
The embodiment of the present invention also provides a kind of device of scheduling virtual machine, including processor and computer-readable storage medium
Matter is stored with instruction in the computer readable storage medium, wherein when described instruction is executed by the processor, realizes
The method of above-mentioned scheduling virtual machine.
The embodiment of the invention also provides a kind of computer readable storage mediums, are stored with computer executable instructions,
The computer executable instructions are performed the method for realizing the scheduling virtual machine.
The migration time that method used in the embodiment of the present invention can select optimal physical machine for virtual machine, reduce virtual machine
Number, improves cloud computing resources utilization rate, and the main performance using time series algorithm analysis physical machine is calculated with improved cluster
Method is that virtual machine selects optimal physical machine node, to avoid the frequent migration of virtual machine, improves resource utilization and cluster
Load equilibrium.
It will appreciated by the skilled person that whole or certain steps, system, dress in method disclosed hereinabove
Functional module/unit in setting may be implemented as software, firmware, hardware and its combination appropriate.In hardware embodiment,
Division between the functional module/unit referred in the above description not necessarily corresponds to the division of physical assemblies；For example, one
Physical assemblies can have multiple functions or a function or step and can be executed by several physical assemblies cooperations.Certain groups
Part or all components may be implemented as by processor, such as the software that digital signal processor or microprocessor execute, or by
It is embodied as hardware, or is implemented as integrated circuit, such as specific integrated circuit.Such software can be distributed in computer-readable
On medium, computer-readable medium may include computer storage medium (or non-transitory medium) and communication media (or temporarily
Property medium).As known to a person of ordinary skill in the art, term computer storage medium is included in for storing information (such as
Computer readable instructions, data structure, program module or other data) any method or technique in the volatibility implemented and non-
Volatibility, removable and nonremovable medium.Computer storage medium include but is not limited to RAM, ROM, EEPROM, flash memory or its
His memory technology, CD-ROM, digital versatile disc (DVD) or other optical disc storages, magnetic holder, tape, disk storage or other
Magnetic memory apparatus or any other medium that can be used for storing desired information and can be accessed by a computer.This
Outside, known to a person of ordinary skill in the art to be, communication media generally comprises computer readable instructions, data structure, program mould
Other data in the modulated data signal of block or such as carrier wave or other transmission mechanisms etc, and may include any information
Delivery media.
Claims (9)
1. a kind of method of scheduling virtual machine characterized by comprising
The performance data of physical machine is analyzed in real time, predicts the performance data of physical machine described in subsequent time；
The performance data of the physical machine subsequent time and the performance data of virtual machine are compared, the performance with the virtual machine is obtained
The maximum physical machine of data difference；
The virtual machine is arranged in acquired physical machine.
2. the method according to claim 1, wherein it is described in real time to the performance data of physical machine carry out analysis be
It is accomplished by the following way:
Time sequence analysis algorithm.
3. method according to claim 1 or 2, which is characterized in that the performance of physical machine described in the prediction subsequent time
Data, comprising:
Predict the service condition of the resource of each dimension of physical machine described in subsequent time.
4. the method according to claim 1, wherein the performance data for comparing the physical machine subsequent time
It is achieved in the following ways with the performance data of virtual machine:
Utilize the clustering algorithm for maximizing difference in class.
5. a kind of device of scheduling virtual machine characterized by comprising
Analysis module predicts the performance of physical machine described in subsequent time for analyzing in real time the performance data of physical machine
Data；
Module is obtained, for comparing the performance data of the physical machine subsequent time and the performance data of virtual machine, acquisition and institute
State the maximum physical machine of performance data difference of virtual machine；
Module is arranged, for the virtual machine to be arranged in acquired physical machine.
6. device according to claim 5, which is characterized in that
The analysis module carries out analysis to the performance data of physical machine in real time and is achieved in the following ways: time series
Parser.
7. device according to claim 5 or 6, which is characterized in that
The analysis module predicts the performance data of physical machine described in subsequent time, comprising: physical machine described in prediction subsequent time
Each dimension resource service condition.
8. device according to claim 5, which is characterized in that
The performance data of the acquisition module, the performance data and virtual machine that compare the physical machine subsequent time is by following
What mode was realized: utilizing the clustering algorithm for maximizing difference in class.
9. a kind of device of scheduling virtual machine, including processor and computer readable storage medium, the computer-readable storage
Instruction is stored in medium, which is characterized in that when described instruction is executed by the processor, realize that claim 1-4 is any
The method of the item scheduling virtual machine.
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