计算机应用 ›› 2020, Vol. 40 ›› Issue (5): 1374-1381.DOI: 10.11772/j.issn.1001-9081.2019081408

• 先进计算 • 上一篇    下一篇

云环境下基于模糊隶属度的虚拟机放置算法

郭曙杰, 李志华, 蔺凯青   

  1. 江南大学 物联网工程学院,江苏 无锡 214122
  • 收稿日期:2019-09-08 修回日期:2019-10-17 出版日期:2020-05-10 发布日期:2020-05-15
  • 通讯作者: 李志华(1969—)
  • 作者简介:郭曙杰(1994—),男,江苏常州人,硕士研究生,CCF会员,主要研究方向:云计算、分布式计算; 李志华(1969—),男,湖南保靖人,副教授,博士,主要研究方向:云计算、信息安全; 蔺凯青(1993—),女,山西吕梁人,硕士研究生,CCF会员,主要研究方向:云计算、分布式计算。
  • 基金资助:

    工业和信息化部智能制造项目(ZH-XZ-180004)。

Fuzzy membership degree based virtual machine placement algorithmin cloud environment

GUO Shujie, LI Zhihua, LIN Kaiqing   

  1. School of Internet of Things Engineering, Jiangnan University, Wuxi Jiangsu 214122, China
  • Received:2019-09-08 Revised:2019-10-17 Online:2020-05-10 Published:2020-05-15
  • Contact: LI Zhihua, born in 1969, Ph. D., associate professor. His research interests include cloud computing, information safety.
  • About author:GUO Shujie, born in 1994, M. S. candidate. His research interests include cloud computing, parallel computing.LI Zhihua, born in 1969, Ph. D., associate professor. His research interests include cloud computing, information safety.LIN Kaiqing, born in 1993, M. S. candidate. Her research interests include cloud computing, distributed computing.
  • Supported by:

    This work is partially supported by the Intelligent Manufacturing Project of Ministry of Industry and Information Technology (ZH-XZ-180004).

摘要:

虚拟机放置问题是云数据中心资源调度的核心问题之一,它对数据中心的性能、资源利用率和能耗有着重要的影响。针对此问题,以降低数据中心能耗、改善资源利用率和保证服务质量(QoS)为优化目标,借助模糊聚类的思想提出了一种基于模糊隶属度的虚拟机放置算法。首先,结合物理主机过载概率和虚拟机与物理主机之间的相适性放置关系,提出了新的距离度量方法;然后,根据模糊隶属度函数计算得出虚拟机与物理主机之间的相适性模糊隶属度矩阵;最后,借助能耗感知机制,在模糊隶属度矩阵中进行局部搜索从而获得迁移虚拟机的最优放置方案。仿真实验结果表明,提出的算法在降低云数据中心能耗、改善资源利用率和保证QoS方面表现比较优异。

关键词: 云计算, 虚拟机放置, 模糊聚类, 模糊隶属度, 服务质量

Abstract:

Virtual machine placement is one of the core problems of resource scheduling in cloud data center. It has an important impact on the performance, resource utilization and energy consumption of data center. In order to optimize the data center energy consumption, improve resource utilization and ensure Quality of Service (QoS), a fuzzy membership degree based virtual machine placement algorithm was proposed. Firstly, combined the overload probability of physical hosts with the fitness placement relationship between virtual machines and physical hosts, a new distance measurement method was proposed. Then, according to the fuzzy membership function, the fitness fuzzy membership matrix between virtual machines and physical hosts was calculated. Finally, with the mechanism of energy awareness, the local search was performed in the fuzzy membership matrix to obtain the optimal placement scheme of the migration virtual machines. Simulation results show that the proposed algorithm can reduce the energy consumption of cloud data center, improve resource utilization and ensure QoS.

Key words: cloud computing, virtual machine placement, fuzzy clustering, fuzzy membership degree, Quality of Service (QoS)

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