| 基于粒子群优化算法的虚拟机放置策略 |
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| 引用本文： | 裴养,吴杰,王鑫.基于粒子群优化算法的虚拟机放置策略[J].计算机工程,2012,38(16):291-292. |
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| 作者姓名： | 裴养 吴杰 王鑫 |
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| 作者单位： | 复旦大学计算机科学技术学院 |
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| 摘 要： | 当前云计算虚拟化平台无法适用于对时延要求较高的应用。为此，提出一种基于粒子群优化算法的虚拟机放置策略。介绍粒子群优化算法，建立云环境内部时延模型，设计虚拟机放置策略架构。实验结果表明，该策略的请求响应时间比动态资源调度(DRS)策略降低14%~19%，每秒处理请求数比DRS方案提高约17%。
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| 关 键 词： | 云计算 虚拟机放置 粒子群优化算法 时延 工作流 |
| 收稿时间： | 2011-10-24 |
| 修稿时间： | 2011-12-08 |
Virtual Machine Placement Strategy Based on Particle Swarm Optimization Algorithm |
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| PEI Yang,WU Jie,WANG Xin.Virtual Machine Placement Strategy Based on Particle Swarm Optimization Algorithm[J].Computer Engineering,2012,38(16):291-292. |
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| Authors: | PEI Yang WU Jie WANG Xin |
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| Affiliation: | (School of Computer Science,Fudan University,Shanghai 200433,China) |
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| Abstract: | Currently,the virtual machine placement strategy of cloud computing perform is not well in the low delay require.In order to solve this problem,this paper proposes a new virtual machine placement strategy based on Particle Swarm Optimization(PSO) algorithm.It introduces the PSO algorithm,designs a delay model in cloud environment,and combines them to get virtual machine placed scheme.Experimental results show that the response time is less than Dynamic Resource Scheduler(DRS) by 14%~19%,and the Requests per Second(RPS) is more by 17%. |
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| Keywords: | cloud computing virtual machine placement Particle Swarm Optimization(PSO) algorithm delay workflow |
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