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A new technique for efficient live migration of multiple virtual machines

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 (Q...

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Bibliographic Details
Published in:Future generation computer systems 2016-02, Vol.55, p.74-86
Main Authors: Sun, Gang, Liao, Dan, Anand, Vishal, Zhao, Dongcheng, Yu, Hongfang
Format: Article
Language:English
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Summary: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. •We propose an improved serial migration strategy for migrating multiple VMs.•We present the m mixed migration strategy for improving the time efficiency.•For a given tolerable downtime, we calculate m to minimize the migration time.•We evaluate the effectiveness of the proposed approach by using queuing models.
ISSN:0167-739X
1872-7115
DOI:10.1016/j.future.2015.09.005