计算机工程 ›› 2012, Vol. 38 ›› Issue (16): 291-292.doi: 10.3969/j.issn.1000-3428.2012.16.076

• 开发研究与设计技术 • 上一篇    

基于粒子群优化算法的虚拟机放置策略

裴 养,吴 杰,王 鑫   

  1. (复旦大学计算机科学技术学院,上海 200433)
  • 收稿日期:2011-10-24 修回日期:2011-12-08 出版日期:2012-08-20 发布日期:2012-08-17
  • 作者简介:裴 养(1986-),男,硕士,主研方向:云计算,虚拟机技术;吴 杰,副教授;王 鑫,硕士

Virtual Machine Placement Strategy Based on Particle Swarm Optimization Algorithm

PEI Yang, WU Jie, WANG Xin   

  1. (School of Computer Science, Fudan University, Shanghai 200433, China)
  • Received:2011-10-24 Revised:2011-12-08 Online:2012-08-20 Published:2012-08-17

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%。

关键词: 云计算, 虚拟机放置, 粒子群优化算法, 时延, 工作流

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%.

Key words: cloud computing, virtual machine placement, Particle Swarm Optimization(PSO) algorithm, delay, workflow

中图分类号: