Journal of Computer Applications ›› 2020, Vol. 40 ›› Issue (6): 1707-1713.DOI: 10.11772/j.issn.1001-9081.2019111988

• Advanced computing • Previous Articles     Next Articles

Greedy algorithm optimization based virtual machine selection strategy in cloud data center

CAI Hao1, YUAN Zhengdao2   

  1. 1. Center of Information Technology, Henan Radio & Television University, Zhengzhou Henan, 450008, China
    2. School of Information and Engineering, Henan Radio & Television University, Zhengzhou Henan, 450001, China
  • Received:2019-11-22 Revised:2019-12-19 Online:2020-06-10 Published:2020-06-18
  • Contact: CAI Hao, born in 1987, M. S., lecturer. His research interests include computer network security, cloud computing.
  • About author:YUAN Zhengdao, born in 1983, Ph. D., lecturer. His research interests include large-scale communication system, communication protocol of Internet of things, wireless sensor network.CAI Hao, born in 1987, M. S., lecturer. His research interests include computer network security, cloud computing.
  • Supported by:
    Training Plan of Young Backbone Teachers in Colleges and Universities of Henan Province (2017GGJS135), the Henan Science and Technology Public Relation Project (182102210573), the Suface Program of China Postdoctoral Science Foundation (2019M652576), the Henan Postdoctoral Science Starting Foundation (19030016).

云数据中心基于贪心模式的虚拟机选择算法

蔡豪1, 袁正道2   

  1. 1.河南广播电视大学 信息技术中心, 郑州 450008
    2.河南广播电视大学 信息工程学院, 郑州 450001
  • 通讯作者: 蔡豪(1987—)
  • 作者简介:蔡豪(1987—),男,河南确山人,讲师,硕士,主要研究方向:计算机网络安全、云计算.袁正道(1983—),男,河南郑州人,讲师,博士,主要研究方向:大规模通信系统、物联网通信协议、无线传感器网络.
  • 基金资助:
    河南省高等学校青年骨干教师培养计划(2017GGJS135);河南省科技攻关项目(182102210573);中国博士后科学基金面上项目(2019M652576);河南省博士后科研基金启动基金资助项目(19030016)。

Abstract: In the virtual machine migration process, one of the most problems is how to select the candidate migrating virtual machine list from the abnormal physical hosts in cloud data center. Therefore, a Greedy Algorithm Optimization based Virtual Machine Selection algorithm (GAO-VMS) was proposed. In GAO-VMS, the virtual machines with the optimal objective functions would be selected to perform the migration and the candidate migration virtual machine list was formed subsequently. There are three kinds of greedy modes in GAO-VMS: Maximum Power Reduction Policy (MPR), minimum migration Time and Power Tradeoff policy (TPT) and Violated million instructions per second-Virtual Machines policy (VVM). GAO-VMS was evaluated on CloudSim simulator. Simulation results show that compared to the common virtual machine migration strategy, GAO-VMS reduces the energy consumption of cloud data center by 30%-35%, and reduces the number of virtual machine migrations by 40%-45% with 5% increment of the Service Level Agreement (SLA) violation rate and the joint index of SLA violation and energy. The proposed GAO-VMS strategy can be used for enterprises to construct green cloud computing center.

Key words: intelligent computing, greedy algorithm, virtual machine selection, cloud data centers, low energy consumption

摘要: 针对如何从云数据中心的异常物理主机中选择出候选迁移虚拟机列表是虚拟机迁移中的问题,提出了基于贪心模式的虚拟机选择算法(GAO-VMS)。GAO-VMS每次都选择那些目标函数最优的虚拟机作为标准来迁移,形成候选迁移虚拟机列表,它有三类贪心模式:最大能量降低消耗策略(MPR)、最小迁移时间及能量消耗均衡策略(TPT)、最小每秒百万条指令数虚拟机请求策略(VVM)。使用CloudSim模拟器作为GAO-VMS的仿真环境。仿真结果表明:与常见的虚拟机迁移策略相比较,GAO-VMS使得云数据中心的能量消耗减少了30%~35%,虚拟机迁移次数减少了40%~45%,服务等级协议(SLA)违规率以及SLA违规和能量消耗联合指标只有5%的增加。GAO-VMS策略可用于企业构造绿色云计算中心。

关键词: 智能计算, 贪心算法, 虚拟机选择, 云数据中心, 低能量消耗

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