Group virtual machine scheduling policy for cloud computing environment

A technology of cloud computing environment and scheduling strategy, applied in the field of cloud computing, can solve the problem of insufficient attention

Inactive Publication Date: 2018-03-02
成都启力慧源科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, in the current virtual machine scheduling algorithm, the attention

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  • Group virtual machine scheduling policy for cloud computing environment
  • Group virtual machine scheduling policy for cloud computing environment
  • Group virtual machine scheduling policy for cloud computing environment

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Embodiment Construction

[0069] In the present invention, the group virtual machine is mainly taken as the research object, and the scheduling policy problem of the group virtual machine under multi-resource constraints is considered. In the scheduling of group virtual machines, the communication efficiency between virtual machines, total network traffic, congestion control, etc. will be mainly considered.

[0070] In order to make the description clearer, four definitions are given below:

[0071] Definition 1: There are M physical machines in the cloud computing environment, denoted as P={P 1 ,P 2 ,...,P m ,…P M}, any physical machine P m The number of available resources (such as CPU, memory, broadband, storage, etc.) is recorded as d, then H i,j Indicates the physical machine P i The capacity of resources of type j, where j≤d.

[0072] Definition 2: The user applies for a group of virtual machines, the number is N, denoted as V={V 1 ,V 2 ,...,V i ,...V N}, the required resource of any v...

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Abstract

The invention discloses a group virtual machine scheduling policy for a cloud computing environment. The policy comprises the following steps of S1, establishing a feasible decision space of virtual machine scheduling; S2, minimizing total flow of a network where group virtual machines are located, and establishing an objective function for optimizing the total flow of the network; S3, minimizinga maximum link utilization rate in the network, and establishing an objective function for optimizing the maximum link utilization rate; and S4, establishing an overall objective function, and solvingthe overall objective function in combination with an ant colony algorithm and a simulated annealing algorithm to obtain an optimal solution of the function and mapping relationships between the virtual machines and a physical machine. Under the condition of fully considering resource constraints, the control of the total flow of the network and the balance of flow distribution on a network linkare defined as a combination optimization problem, and solving is performed in combination with the ant colony algorithm and the simulated annealing algorithm. According to the scheduling policy provided by the invention, the performance of the network where the group virtual machines are located can be better optimized; the congestion is reduced; and the service quality of users is effectively improved.

Description

technical field [0001] The invention belongs to the technical field of cloud computing, and in particular relates to a group virtual machine scheduling strategy in a cloud computing environment. Background technique [0002] In the cloud computing environment, the underlying physical resources are mainly allocated, managed, and scheduled through virtualization technology, and virtual machines, as the main carrier after virtualization of physical devices, can map resources through different mappings with physical resources. Perform unified management and dynamic deployment to provide users with transparent services. [0003] A group virtual machine is a group of associated virtual machines selected by a user request. The association here mainly refers to resource constraints or dependencies among virtual machines or components of virtual machines. Group virtual machines can be deployed on the same or multiple physical machines. The related mapping relationship is related to ...

Claims

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Application Information

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IPC IPC(8): G06F9/455G06N3/00
CPCG06F9/45558G06F2009/4557G06F2009/45595G06N3/006
Inventor 贺丽荣盛泳潘
Owner 成都启力慧源科技有限公司
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