• DocumentCode
    2549255
  • Title

    Exploiting Data Deduplication to Accelerate Live Virtual Machine Migration

  • Author

    Zhang, Xiang ; Huo, Zhigang ; Ma, Jie ; Meng, Dan

  • Author_Institution
    Nat. Res. Center for Intell. Comput. Syst., Chinese Acad. of Sci., Beijing, China
  • fYear
    2010
  • fDate
    20-24 Sept. 2010
  • Firstpage
    88
  • Lastpage
    96
  • Abstract
    As one of the key characteristics of virtualization, live virtual machine (VM) migration provides great benefits for load balancing, power management, fault tolerance and other system maintenance issues in modern clusters and data centers. Although Pre-Copy is a widespread used migration algorithm, it does transfer a lot of duplicated memory image data from source to destination, which results in longer migration time and downtime. This paper proposes a novel VM migration approach, named Migration with Data Deduplication (MDD), which introduces data deduplication into migration. MDD utilizes the self-similarity of run-time memory image, uses hash based fingerprints to find identical and similar memory pages, and employs Run Length Encode (RLE) to eliminate redundant memory data during migration. Experiment demonstrates that compared with Xen´s default Pre-Copy migration algorithm, MDD can reduce 56.60% of total data transferred during migration, 34.93% of total migration time, and 26.16% of downtime on average.
  • Keywords
    resource allocation; storage area networks; storage management; virtual machines; workstation clusters; data centers; data deduplication; duplicated memory image data; fault tolerance; hash based fingerprint; live virtual machine migration; load balancing; power management; redundant memory data elimination; run length encode; run-time memory image; self-similarity; system maintenance; Acceleration; Bandwidth; Banking; Encoding; Fingerprint recognition; Instruction sets; Memory management; data deduplication; live migration; virtualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster Computing (CLUSTER), 2010 IEEE International Conference on
  • Conference_Location
    Heraklion, Crete
  • Print_ISBN
    978-1-4244-8373-0
  • Electronic_ISBN
    978-0-7695-4220-1
  • Type

    conf

  • DOI
    10.1109/CLUSTER.2010.17
  • Filename
    5600319