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Journal of Software:2014.25(7):1388-1402

资源调度等待开销感知的虚拟机整合
李铭夫,毕经平,李忠诚
(中国科学院 计算技术研究所, 北京 100190)
Resource-Scheduling-Waiting-Aware Virtual Machine Consolidation
LI Ming-Fu,BI Jing-Ping,LI Zhong-Cheng
(Institute of Computing Technology, The Chinese Academy of Sciences, Beijing 100190, China)
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Received:October 31, 2013    Revised:May 06, 2014
> 中文摘要: 近年来,数据中心庞大的能源开销问题引起广泛关注.虚拟化管理平台可以通过虚拟机迁移技术将虚拟机整合到更少的服务器上,从而提高数据中心能源有效性.对面向数据中心节能的虚拟机整合研究工作进行调研,并总结虚拟机整合研究存在的3个挑战.针对已有工作未考虑虚拟机等待资源调度带来的服务器资源额外开销这种现象,开展了资源调度等待开销感知的虚拟机整合研究.从理论和实验上证明了在具有实际意义的约束条件下,存在着虚拟机等待资源调度带来的服务器资源额外开销,且随着整合虚拟机数量的增长保持稳定.基于典型工作负载的实验结果表明,这个额外开销平均占据了11.7%的服务器资源开销.此外,提出了资源预留整合(MRC)算法,用于改进已有的虚拟机整合算法.算法模拟实验结果表明,MRC算法相比于常用的虚拟机整合算法FFD(first fit decreasing),明显降低了服务器资源溢出概率.
Abstract:In recent years, the huge resource consumption problem of data centers is being widely concerned. Virtual machine monitor (VMM) can consolidate virtual machines (VMs) onto fewer servers via VM migration to improve the energy efficiency of data centers. This paper surveys the recent works on energy-efficient VM consolidation, and summarizes three research challenges. Among them, this work considers the resource consumption overhead caused by the waiting of virtual machines for server resource scheduling. The study theoretically and experimentally proves that under realistic constraints, this overhead remains steady as the number of consolidating VMs grows. Experiments based on a representative benchmark show that, on average, 11.7% of the server's CPU resource is occupied by the overhead. In addition, in order to fill in the gap on existing approaches, this paper proposes margin reserved consolidation (MRC) algorithm. Simulation results show that MRC outperforms the state of the art baseline in terms of server resource violation probability.
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基金项目:国家重点基础研究发展计划(973)(2011302505);国家自然科学基金(61070210,61303243) 国家重点基础研究发展计划(973)(2011302505);国家自然科学基金(61070210,61303243)
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李铭夫,毕经平,李忠诚.资源调度等待开销感知的虚拟机整合.软件学报,2014,25(7):1388-1402

LI Ming-Fu,BI Jing-Ping,LI Zhong-Cheng.Resource-Scheduling-Waiting-Aware Virtual Machine Consolidation.Journal of Software,2014,25(7):1388-1402