CN113282369A - Virtual machine scheduling method, device, medium and equipment - Google Patents

Virtual machine scheduling method, device, medium and equipment Download PDF

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CN113282369A
CN113282369A CN202110577188.6A CN202110577188A CN113282369A CN 113282369 A CN113282369 A CN 113282369A CN 202110577188 A CN202110577188 A CN 202110577188A CN 113282369 A CN113282369 A CN 113282369A
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physical node
virtual machine
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CN113282369B (en
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董隽雄
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Inesa R&d Center
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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
    • G06F9/50—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
    • G06F9/5011—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals
    • G06F9/5016—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals the resource being the memory
    • 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
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • 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]
    • G06F9/5061—Partitioning or combining of resources
    • G06F9/5072—Grid computing
    • 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

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Abstract

The invention relates to a method, a device, a medium and equipment for scheduling a virtual machine, wherein the scheduling method specifically comprises the following steps: receiving a request instruction of a newly added virtual machine; acquiring the proportion of the used CPU and the used memory of each physical node in the cloud platform, and calculating the used resource offset of each physical node; calculating the resource expected offset of each physical node when the newly-added virtual machine is added; calculating the newly increased stability of each physical node based on the used offset of the resource and the predicted offset of the resource; selecting a physical node with positive newly added stability as a candidate physical node; and determining the physical node with the maximum newly-added stability in the candidate physical nodes as the physical node to be scheduled of the newly-added virtual machine, and scheduling the newly-added virtual machine to the physical node. Compared with the prior art, the invention can effectively reduce the waste of resources on the physical node caused by uneven distribution.

Description

Virtual machine scheduling method, device, medium and equipment
Technical Field
The invention belongs to the technical field of cloud computing, relates to a virtual machine scheduling method, and particularly relates to a virtual machine scheduling method for reducing resource waste of physical nodes.
Background
Nowadays, with the development of cloud computing, various traditional manufacturers have migrated traditional applications on original physical machines to the cloud. The most important scheduling in the cloud computing platform is the scheduling of the virtual machine, and the essence of the scheduling of the virtual machine is the scheduling of two computing resources, namely a CPU and a memory, how to select a proper physical node to run the virtual machine will determine the resource rate of the whole cloud platform, and the scheduling of the virtual machine on the cloud platform generally has the following characteristics:
1) the difference between the CPU and memory ratios of the demands is large
The specifications of virtual machines required by different customers are different, and the quantity of required computing resources is also different according to the characteristics of the services, so that the ratio difference between the two is huge.
2) Invariability of physical nodes
The resource quantity of the physical node is generally in an invariable state, and the CPU and the memory cannot be changed after the physical node is put into formal use, so the ratio of the CPU and the memory on the physical machine can be considered to be invariable.
3) Virtual machines may not be able to be live migrated
Part of customer service is in a busy state from the beginning of operation, the customer is unwilling to temporarily interrupt the service, the busy degree of the virtual machine does not meet the idle requirement of live migration, and the virtual machine is not easy to be dispatched to other nodes by a method of live migration of the virtual machine.
The current general virtual machine scheduling algorithm is to calculate the sum of weighted most absolute values of the idle quantities of various resources (CPUs and memories) on various physical nodes, and finally select the physical node with the highest sum to operate the virtual machine. Therefore, when a certain resource of the physical node is idle more, and a newly started virtual machine needs less resource, the newly started virtual machine is continuously scheduled to the physical node, and another resource is exhausted, and finally the resource on the node is wasted too much.
Disclosure of Invention
The present invention aims to overcome the above-mentioned defects in the prior art, and provides a virtual machine scheduling method, medium, and electronic device, which implement virtual machine scheduling by combining the physical node computing resource proportion and the newly started virtual machine computing resource proportion, and effectively reduce the waste of resources on the physical node due to uneven allocation.
The purpose of the invention can be realized by the following technical scheme:
a virtual machine scheduling method for reducing resource waste of physical nodes is characterized in that a physical node to be scheduled of a newly-added virtual machine is determined based on the proportion of a used CPU (Central processing Unit) and a used memory of each physical node in a cloud platform, the newly-added virtual machine is scheduled to the physical node, and the determined proportion of the used CPU and the used memory of the physical node is closest to the proportion of a total CPU and a total memory of the physical node, and the method specifically comprises the following steps:
receiving a request instruction of a newly added virtual machine;
obtaining the proportion of the used CPU and the used memory of each physical node in the cloud platform, and calculating the used resource offset O of each physical nodeHas already been used for；
Calculating the resource predicted offset O of each physical node when the newly-added virtual machine is addedPreparation of；
Calculating newly-added stability S, S ═ O of each physical node based on the resource used offset and the resource predicted offsetHas already been used for-OPreparation of；
Selecting a physical node with positive newly added stability as a candidate physical node;
and determining the physical node with the maximum newly-added stability S in the candidate physical nodes as a physical node to be scheduled of the newly-added virtual machine, and scheduling the newly-added virtual machine to the physical node.
Further, the resource has used an offset OHas already been used forThe calculation formula of (2) is as follows:
Figure BDA0003084843280000021
in the formula, CHas already been used forNumber of used CPUs for a physical node, MHas already been used forIs the amount of used memory of the physical node, CGeneral assemblyIs the total CPU number of the physical node, MGeneral assemblyIs the total memory amount of the physical node.
Further, the resource has used an offset OHas already been used forThe calculation formula of (2) is as follows:
Figure BDA0003084843280000022
in the formula, CHas already been used forNumber of used CPUs for a physical node, MHas already been used forIs the amount of used memory of the physical node, CGeneral assemblyIs the total CPU number of the physical node, MGeneral assemblyIs the total memory amount of the physical node, CNewNumber of CPUs requested for newly added virtual machines, MNewThe amount of memory required for the newly added virtual machine.
Further, the method further comprises:
after receiving a request instruction of a newly added virtual machine, judging whether the residual resources of each physical node of the cloud platform meet the request of the newly added virtual machine, if so, retaining the corresponding physical node, and if not, rejecting the corresponding physical node.
The invention also provides a virtual machine scheduling device for reducing the resource waste of physical nodes, which comprises:
the instruction receiving module is used for receiving a request instruction of the newly added virtual machine;
a first computing module, configured to obtain a ratio of a used CPU to a used memory of each physical node in the cloud platform, and compute a resource used offset O of each physical nodeHas already been used for；
A second calculation module, configured to calculate a resource expected offset O of each physical node when the newly-added virtual machine is addedPreparation of；
A third calculating module, configured to calculate a newly added stability S, S ═ O for each physical node based on the resource used offset and the resource expected offsetHas already been used for-OPreparation of；
The selecting module is used for selecting the physical node with positive newly added stability as a candidate physical node;
and the scheduling module is used for determining the physical node with the maximum newly-added stability S in the candidate physical nodes as the physical node to be scheduled by the newly-added virtual machine and scheduling the newly-added virtual machine to the physical node.
Further, in the first computing module, the resource has used an offset OHas already been used forThe calculation formula of (2) is as follows:
Figure BDA0003084843280000031
in the formula, CHas already been used forNumber of used CPUs for a physical node, MHas already been used forIs the amount of used memory of the physical node, CGeneral assemblyIs the total CPU number of the physical node, MGeneral assemblyIs the total memory amount of the physical node.
Further, in the second computing module, the resource has used an offset OHas already been used forThe calculation formula of (2) is as follows:
Figure BDA0003084843280000032
in the formula, CHas already been used forNumber of used CPUs for a physical node, MHas already been used forIs the amount of used memory of the physical node, CGeneral assemblyIs the total CPU number of the physical node, MGeneral assemblyIs the total memory amount of the physical node, CNewNumber of CPUs requested for newly added virtual machines, MNewThe amount of memory required for the newly added virtual machine.
Further, the scheduling apparatus further includes:
and the removing module is used for judging whether the residual resources of each physical node of the cloud platform meet the requirement of the newly added virtual machine, if so, retaining the corresponding physical node, otherwise, removing the corresponding physical node, and transmitting the retained physical node information to the first computing module and the second computing module.
The present invention also provides a computer readable storage medium comprising one or more programs for execution by one or more processors of an electronic device, the one or more programs including instructions for performing the virtual machine scheduling method for reducing physical node resource waste as described above.
The present invention also provides an electronic device comprising:
one or more processors;
a memory; and
one or more programs stored in the memory, the one or more programs including instructions for performing the virtual machine scheduling method that reduces physical node resource waste as described above.
Compared with the prior art, the invention has the following beneficial effects:
1. the method selects the physical node which enables the proportion of the number of the used CPUs to the number of the used memories to be as close as possible to the proportion of the number of the total CPUs to the number of the total memories as the scheduling node of the newly-added virtual machine, and when the computing node of the whole cluster is large enough, the proportion of the used CPUs to the used memories of all the physical nodes is close to the proportion of the number of the total CPUs to the number of the total memories, so that the waste of computing resources is effectively reduced, and the resource utilization rate is improved.
2. The invention calculates the quantity of the CPU and the memory, is convenient for data acquisition and simple in calculation, and improves the scheduling efficiency.
3. Before each physical node is calculated, whether the newly added requirement is met or not is judged, the calculated amount is reduced, and the scheduling efficiency is further improved.
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FIG. 1 is a schematic flow chart of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
The embodiment provides a virtual machine scheduling method for reducing resource waste of physical nodes, which includes determining a physical node to be scheduled of a newly-added virtual machine based on a ratio of a used CPU to a used memory of each physical node in a cloud platform, scheduling the newly-added virtual machine to the physical node, wherein the determined ratio of the used CPU to the used memory of the physical node is closest to a ratio of a total CPU to a total memory of the physical node, so as to reduce resource waste as much as possible.
Referring to fig. 1, the method specifically includes the following steps:
and S1, receiving a request instruction of the newly added virtual machine, wherein the request of the newly added virtual machine comprises the quantity of CPUs and the quantity of memories requested by the newly added virtual machine.
And S2, calculating the newly added stability of each physical node.
a. Obtaining the proportion of the used CPU and the used memory of each physical node in the cloud platform, and calculating the used resource offset O of each physical nodeHas already been used for：
Figure BDA0003084843280000051
In the formula, CHas already been used forNumber of used CPUs for a physical node, MHas already been used forIs the amount of used memory of the physical node, CGeneral assemblyIs the total CPU number of the physical node, MGeneral assemblyIs the total memory amount of the physical node.
b. Calculating the resource predicted offset O of each physical node when the newly-added virtual machine is addedPreparation of：
Figure BDA0003084843280000052
In the formula, CNewNumber of CPUs requested for newly added virtual machines, MNewThe amount of memory required for the newly added virtual machine.
c. Calculating newly-added stability S, S ═ O of each physical node based on the resource used offset and the resource predicted offsetHas already been used for-OPreparation of。
And S3, finishing the scheduling of the newly added virtual machine.
If the newly added stability calculated in step S2 is a positive number, it means that scheduling a new virtual machine to a corresponding physical node can increase the resource allocation stability of the physical node, and reduce resource waste, otherwise, a physical node with the newly added stability of a positive number is selected as a candidate physical node.
And comparing the magnitude of the newly-increased stability of each candidate physical node, determining the physical node with the maximum newly-increased stability in the candidate physical nodes as a to-be-scheduled physical node of the newly-increased virtual machine, scheduling the newly-increased virtual machine to the physical node, and starting the virtual machine.
Referring to fig. 1, in a preferred embodiment, the method further comprises:
s4, after receiving the request instruction of the newly added virtual machine, firstly judging whether the residual resources of each physical node of the cloud platform meet the request of the newly added virtual machine, namely judging whether the residual memory and CPU of each node are both more than CNewAnd MNewIf yes, the corresponding physical node is reserved, and if not, the corresponding physical node is removed to reduce the calculation amount.
The above functions, if implemented in the form of software functional units and sold or used as a separate product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another embodiment, a virtual machine scheduling apparatus for reducing resource waste of physical nodes is also provided.
In another embodiment, there is also provided an electronic device comprising one or more processors, memory, and one or more programs stored in the memory, the one or more programs including instructions for performing the scheduling method as described above.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.

Claims (10)

1. A virtual machine scheduling method for reducing resource waste of physical nodes is characterized in that the method determines physical nodes to be scheduled of a newly-added virtual machine based on the proportion of used CPUs (central processing units) and used memories of all physical nodes in a cloud platform, schedules the newly-added virtual machine to the physical nodes, and the determined proportion of the used CPUs and the used memories of the physical nodes is closest to the proportion of total CPUs and total memories of the physical nodes, and specifically comprises the following steps:
receiving a request instruction of a newly added virtual machine;
obtaining the proportion of the used CPU and the used memory of each physical node in the cloud platform, and calculating the used resource offset O of each physical nodeHas already been used for；
Calculating the resource predicted offset O of each physical node when the newly-added virtual machine is addedPreparation of；
Calculating newly-added stability S, S ═ O of each physical node based on the resource used offset and the resource predicted offsetHas already been used for-OPreparation of；
Selecting a physical node with positive newly added stability as a candidate physical node;
and determining the physical node with the maximum newly-added stability S in the candidate physical nodes as a physical node to be scheduled of the newly-added virtual machine, and scheduling the newly-added virtual machine to the physical node.
2. The virtual machine scheduling method for reducing physical node resource waste according to claim 1 wherein the resource has used an offset OHas already been used forThe calculation formula of (2) is as follows:
Figure FDA0003084843270000011
in the formula, CHas already been used forNumber of used CPUs for a physical node, MHas already been used forIs the amount of used memory of the physical node, CGeneral assemblyIs the total CPU number of the physical node, MGeneral assemblyIs the total memory amount of the physical node.
3. The virtual machine scheduling method for reducing physical node resource waste according to claim 1 wherein the resource has used an offset OHas already been used forThe calculation formula of (2) is as follows:
Figure FDA0003084843270000012
in the formula, CHas already been used forNumber of used CPUs for a physical node, MHas already been used forIs the amount of used memory of the physical node, CGeneral assemblyIs the total CPU number of the physical node, MGeneral assemblyIs the total memory amount of the physical node, CNewNumber of CPUs requested for newly added virtual machines, MNewThe amount of memory required for the newly added virtual machine.
4. The virtual machine scheduling method for reducing resource waste of physical nodes according to claim 1, the method further comprising:
after receiving a request instruction of a newly added virtual machine, judging whether the residual resources of each physical node of the cloud platform meet the request of the newly added virtual machine, if so, retaining the corresponding physical node, and if not, rejecting the corresponding physical node.
5. A virtual machine scheduling device for reducing resource waste of physical nodes is characterized by comprising:
the instruction receiving module is used for receiving a request instruction of the newly added virtual machine;
a first computing module, configured to obtain a ratio of a used CPU to a used memory of each physical node in the cloud platform, and compute a resource used offset O of each physical nodeHas already been used for；
A second calculation module, configured to calculate a resource expected offset O of each physical node when the newly-added virtual machine is addedPreparation of；
Third calculationMeans for calculating a newly added stability S, S ═ O for each physical node based on the resource used offset and the resource expected offsetHas already been used for-OPreparation of；
The selecting module is used for selecting the physical node with positive newly added stability as a candidate physical node;
and the scheduling module is used for determining the physical node with the maximum newly-added stability S in the candidate physical nodes as the physical node to be scheduled by the newly-added virtual machine and scheduling the newly-added virtual machine to the physical node.
6. The virtual machine scheduling apparatus for reducing resource waste of physical nodes as claimed in claim 5 wherein, in the first computing module, the resource used offset O isHas already been used forThe calculation formula of (2) is as follows:
Figure FDA0003084843270000021
in the formula, CHas already been used forNumber of used CPUs for a physical node, MHas already been used forIs the amount of used memory of the physical node, CGeneral assemblyIs the total CPU number of the physical node, MGeneral assemblyIs the total memory amount of the physical node.
7. The virtual machine scheduling apparatus for reducing resource waste of physical nodes as claimed in claim 5, wherein in the second computing module, the resource used offset O isHas already been used forThe calculation formula of (2) is as follows:
Figure FDA0003084843270000022
in the formula, CHas already been used forNumber of used CPUs for a physical node, MHas already been used forIs the amount of used memory of the physical node, CGeneral assemblyIs the total CPU number of the physical node, MGeneral assemblyIs the total memory amount of the physical node, CNewNumber of CPUs requested for newly added virtual machines, MNewTo newly addThe amount of memory requested by the virtual machine.
8. The virtual machine scheduling apparatus for reducing resource waste of a physical node according to claim 5, further comprising:
and the removing module is used for judging whether the residual resources of each physical node of the cloud platform meet the requirement of the newly added virtual machine, if so, retaining the corresponding physical node, otherwise, removing the corresponding physical node, and transmitting the retained physical node information to the first computing module and the second computing module.
9. A computer-readable storage medium comprising one or more programs for execution by one or more processors of an electronic device, the one or more programs including instructions for performing the virtual machine scheduling method of reducing physical node resource waste of any of claims 1-4.
10. An electronic device, comprising:
one or more processors;
a memory; and
one or more programs stored in the memory, the one or more programs including instructions for performing the virtual machine scheduling method of reducing physical node resource waste as claimed in any of claims 1-4.
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