Live Migration for Multiple Correlated Virtual Machines in Cloud-based Data Centers

Gang Sun, Dan Liao, Dongcheng Zhao, Zichuan (Edward) Xu, Hongfang Yu

    Research output: Contribution to journalArticlepeer-review

    Abstract

    With the development of cloud computing, virtual machine migration is emerging as a promising technique to save energy, enhance resource utilizations, and guarantee Quality of Service (QoS) in cloud datacenters. Most of existing studies on the virtual machine migration, however are based on a single virtual machine migration. Although there are some researches on multiple virtual machines migration, the author usually does not consider the correlation among these virtual machines. In practice, in order to save energy and maintain system performance, cloud providers usually need to migrate multiple correlated virtual machines or migrate the entire virtual datacenter (VDC) request. In this paper, we focus on the efficient online live migration of multiple correlated VMs in VDC requests, for optimizing the migration performance. To solve this problem, we propose an efficient VDC migration algorithm (VDC-M). We use the US-wide NSF network as substrate network to conduct extensive simulation experiments. Simulation results show that the performance of the proposed algorithm is promising in terms of the total VDC remapping cost, the blocking ratio, the average migration time and the average downtime.
    Original languageEnglish
    JournalIEEE Transactions on Services Computing
    Volumeonline
    DOIs
    Publication statusPublished - 2015

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