A new technique for efficient live migration of multiple virtual machines

被引:82
作者
Sun, Gang [1 ]
Liao, Dan [1 ,2 ]
Anand, Vishal [3 ]
Zhao, Dongcheng [1 ]
Yu, Hongfang [1 ]
机构
[1] Univ Elect Sci & Technol China, Minist Educ, Key Lab Opt Fiber Sensing & Commun, Chengdu 610054, Peoples R China
[2] Univ Elect Sci & Technol China, Inst Elect & Informat Engn Dongguan, Chengdu 610054, Peoples R China
[3] SUNY Coll Brockport, Dept Comp Sci, Brockport, NY USA
来源
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2016年 / 55卷
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Virtual machine; Live migration; Queuing model; Virtualization; Cloud computing;
D O I
10.1016/j.future.2015.09.005
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Datacenter virtualization technologies have attracted a lot of attention to enable various cloud computing services and to facilitate virtual machine (VM) migration. VM migration can help service providers to achieve the goals of saving energy, enhancing resource efficiency and quality of service (QoS). In order to ensure the QoS, the migration time and the downtime of VM should be considered while implementing the VM migration. Most researches focus on the issue of single VM migration by using the post-copy migration strategy or pre-copy migration strategy. However, there is few research that focuses on the problem of live migration for multiple VMs. Therefore, in this paper, we first propose an improved serial migration strategy and introduce the post-copy migration scheme into it. We then propose the m mixed migration strategy that is based on the improved serial migration strategy and the parallel migration strategy. Furthermore, we develop queuing models (i.e., the M/M/C/C and the M/M/C queuing models) to quantify performance metrics, such as the blocking ratio and average waiting time of each migration request. We evaluate the performance of the proposed migration strategy by conducting mathematical analysis, the numerical results show that our proposed strategy outperforms the existing approach. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:74 / 86
页数:13
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