Multi-objective optimization virtual machine placing method under cloud environment

A multi-objective optimization, virtual machine technology, applied in the field of virtual machine placement

Inactive Publication Date: 2014-09-24
HANGZHOU DIANZI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In this regard, power management in cloud data centers becomes an important issue as it dominates the operating costs
In addition, the

Method used

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  • Multi-objective optimization virtual machine placing method under cloud environment
  • Multi-objective optimization virtual machine placing method under cloud environment
  • Multi-objective optimization virtual machine placing method under cloud environment

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Embodiment Construction

[0034] The present invention will be further described in detail below in conjunction with the accompanying drawings and implementation methods.

[0035] refer to figure 1 Execute steps to illustrate the implementation process of the present invention:

[0036] 1. Pheromone collection and heuristic information search

[0037] use τ i,j to represent the pheromone concentration when the virtual machine i is placed on the host j. During the initialization process, the initial pheromone concentration can be passed by τ 0 =1 / [n·(P'(S 0 )+W(S 0 ))] calculated, where n represents the number of virtual machines, S 0 is calculated by FFD algorithm, W(S 0 ) means the value is S 0 The resource waste of the time host, P'(S 0 ) indicates that under normal circumstances the value is S 0 The power consumption at , can be calculated by the following formula:

[0038] P ′ ( S 0 ...

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Abstract

The invention discloses a multi-objective optimization virtual machine placing method under the cloud environment. According to the method provided by the invention, firstly, initializing various parameters in an improved ant colony algorithm, wherein the number of ants NA is included; secondly, sorting a server list in a random arrangement manner, and selecting a new server to perform the virtual machine placing from servers; thirdly, using the formula to calculate the server which is the most valuable server to be placed into a virtual machine based on the all servers which can be placed into the virtual machine, and placing the virtual machine on the current server; lastly, repeating the former step until the resource of the current server cannot meet resource needs of all virtual machines required to be placed. According to the method provided by the invention, the virtual machine placement problem serves as a multi-objective combinational optimization problem, and meanwhile, resource usage and power consumption of a physical machine during running of the virtual machine are taken into account. Compared to other solutions, the method can better improve the resource utilization of a physical server and reduce the power consumption of the physical server.

Description

technical field [0001] The invention relates to a virtual machine placement method based on multi-objective optimization in a cloud environment. Background technique [0002] In recent years, cloud computing has become a popular computing model, which is generally used to host virtual machines and provide services on the Internet. There are three main types of cloud computing: infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS). The adoption and deployment of cloud computing platform is mainly due to its many attractive advantages, such as reliability, quality of service and robustness. For consumers, the resources of the cloud computing platform seem to be unlimited, as long as they need, they can buy as many computing resources as they want. From the supplier's point of view, the key problem that cloud computing platforms need to solve is how to reduce operating costs and maximize profits. In this regard, power management in...

Claims

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Application Information

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IPC IPC(8): G06F9/455G06F9/50
CPCY02D10/00
Inventor 张纪林万健陈恂任永坚任祖杰殷昱煜蒋从锋周丽
Owner HANGZHOU DIANZI UNIV
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