云计算中虚拟机资源分配算法

为了解决云计算中虚拟机部署预留方案浪费大量资源和单目标部署方案不够全面问题，提出了一种基于组的多目标遗传算法虚拟机资源分配算法。该算法分成组编码和资源编码，资源编码根据虚拟机历史资源需求进行整合编码，通过改进的交叉和变异操作，将物理机器个数和虚拟机占用物理机器资源整合。实验结果表明，该算法有效减少了物理机器个数使用和提高了物理机器资源使用率，达到了节能目的。...

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Bibliographic Details
Published in计算机应用研究 Vol. 31; no. 9; pp. 2584 - 2587
Main Author 陈小娇 陈世平 方芳
Format Journal Article
LanguageChinese
Published 上海理工大学光电信息与计算机工程学院,200093%上海理工大学光电信息与计算机工程学院,200093 2014
上海理工大学信息化办公室,200093%上海理工大学信息化办公室,200093
Subjects
云计算
节能
虚拟化
资源分配
遗传算法
遗传算法
资源分配
resource allocation
virtualization
虚拟化
节能
genetic algorithms
cloud computing
云计算
energy-saving
Online AccessGet full text
ISSN1001-3695
DOI10.3969/j.issn.1001-3695.2014.09.005

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Summary:为了解决云计算中虚拟机部署预留方案浪费大量资源和单目标部署方案不够全面问题，提出了一种基于组的多目标遗传算法虚拟机资源分配算法。该算法分成组编码和资源编码，资源编码根据虚拟机历史资源需求进行整合编码，通过改进的交叉和变异操作，将物理机器个数和虚拟机占用物理机器资源整合。实验结果表明，该算法有效减少了物理机器个数使用和提高了物理机器资源使用率，达到了节能目的。
Bibliography:51-1196/TP
cloud computing ; resource allocation ; virtualization ; energy-saving ; genetic algorithms
To resolve the problem that virtual machine deployment reservation scheme wastes a lot of resources and single-ob- jective deployment algorithm is not comprehensive, this paper proposed a virtual machine resource allocation algorithm based on virtual machine group multi-objective genetic algorithm. The algorithm was divided into group coding and resources coding. Resources coding integrated coding according to need of the history resource of virtual machine to physical machine and inte- grated number of physical machine and resource need of physical machine occupied by virtual machine through improved cross- over and mutation operations. The experimental results show that the algorithm is effective to reduce the number of physical machine and resource utilization of physical machine, saving energy as much as possible.
CHEN Xiao-jiao, CHEN Shi-ping, FANG Fang （ a. School of Optical-Electrical ＆ Computer Engineer
ISSN:1001-3695
DOI:10.3969/j.issn.1001-3695.2014.09.005