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基于动态规划的虚拟机放置策略
引用本文:张勋,顾春华,罗飞,常耀辉,文赓.基于动态规划的虚拟机放置策略[J].计算机科学,2017,44(8):54-59, 75.
作者姓名:张勋  顾春华  罗飞  常耀辉  文赓
作者单位:华东理工大学信息科学与工程学院 上海200237,华东理工大学信息科学与工程学院 上海200237,华东理工大学信息科学与工程学院 上海200237,华东理工大学信息科学与工程学院 上海200237;石河子大学信息科学与技术学院 石河子832003,上海电力学院计算机科学与工程学院 上海200090
基金项目:本文受国家自然科学基金项目(61472139)资助
摘    要:在IaaS云环境中,资源的分配管理关键取决于如何放置虚拟机,不当的放置策略可造成资源的损耗以及更多的能耗开销。为了降低整个数据中心的资源损耗和能耗开销,建立一个多目标优化的问题模型,并提出了一种基于动态规划思想的虚拟机放置策略。策略将放置问题转化为多阶段决策的背包问题,利用动态规划的思想把背包问题划分成一系列规模更小的子问题,通过求解子问题的最优解得到原问题的最优解。仿真实验表明,该策略能大大降低数据中心的能耗,并减少资源损耗。

关 键 词:云环境  资源损耗  能耗开销  多目标优化  动态规划
收稿时间:2016/7/19 0:00:00
修稿时间:2016/11/7 0:00:00

Virtual Machine Placement Strategy Based on Dynamic Programming
ZHANG Xun,GU Chun-hu,LUO Fei,CHANG Yao-hui and WEN Geng.Virtual Machine Placement Strategy Based on Dynamic Programming[J].Computer Science,2017,44(8):54-59, 75.
Authors:ZHANG Xun  GU Chun-hu  LUO Fei  CHANG Yao-hui and WEN Geng
Affiliation:School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China,School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China,School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China,School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China;College of Information Science and Technology,Shihezi University,Shihezi 832003,China and School of Computer Science and Engineering,Shanghai University of Electric Power,Shanghai 200090,China
Abstract:In the environment of IaaS cloud,the key factor of the resource allocation management is how to place virtual machine.It is mostly probably that an improper placement strategy may cause the loss of resource and more energy consumption.Thus,a multi-objective optimization model was established which devotes to reduce the resource loss and energy consumption of the whole data center.Further more,a kind of placement strategy about virtual machine based on dynamic programming theory was proposed.In the strategy,the problem of placement is transformed into a knapsack problem of multi-stage decision,in which the knapsack problem is divided into a series of smaller sub-problems with the idea of dynamic programming.And the optimal solution of the original problem is obtained through solving the optimal solution of the sub-problems.Finally,the simulation experiment shows that this strategy can greatly reduce the energy consumption and the resource loss of data center.
Keywords:Cloud environment  Resource loss  Energy consumption  Multi-objective optimization  Dynamic programming
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