• DocumentCode
    1796792
  • Title

    Scalable Traffic-Aware Virtual Machine Management for Cloud Data Centers

  • Author

    Fung Po Tso ; Oikonomou, Kleomenis ; Kavvadia, Eleni ; Pezaros, Dimitrios P.

  • Author_Institution
    Sch. of Comput. Sci., Univ. of Glasgow, Glasgow, UK
  • fYear
    2014
  • fDate
    June 30 2014-July 3 2014
  • Firstpage
    238
  • Lastpage
    247
  • Abstract
    Virtual Machine (VM) management is a powerful mechanism for providing elastic services over Cloud Data Centers (DC)s. At the same time, the resulting network congestion has been repeatedly reported as the main bottleneck in DCs, even when the overall resource utilization of the infrastructure remains low. However, most current VM management strategies are traffic-agnostic, while the few that are traffic-aware only concern a static initial allocation, ignore bandwidth oversubscription, or do not scale. In this paper we present S-CORE, a scalable VM migration algorithm to dynamically reallocate VMs to servers while minimizing the overall communication footprint of active traffic flows. We formulate the aggregate VM communication as an optimization problem and we then define a novel distributed migration scheme that iteratively adapts to dynamic traffic changes. Through extensive simulation and implementation results, we show that S-CORE achieves significant (up to 87%) communication cost reduction while incurring minimal overhead and downtime.
  • Keywords
    cloud computing; optimisation; virtual machines; S-CORE; VM management; cloud data center; distributed migration scheme; elastic services; network congestion; optimization problem; scalable VM migration algorithm; scalable traffic-aware virtual machine management; Bandwidth; Dynamic scheduling; IP networks; Resource management; Servers; Topology; Virtual machine monitors; Communication Cost; Consolidation; Data Center Network; Migration; Scalable; Traffic-Aware; Virtual Machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Distributed Computing Systems (ICDCS), 2014 IEEE 34th International Conference on
  • Conference_Location
    Madrid
  • ISSN
    1063-6927
  • Print_ISBN
    978-1-4799-5168-0
  • Type

    conf

  • DOI
    10.1109/ICDCS.2014.32
  • Filename
    6888900