• DocumentCode
    1938408
  • Title

    Dynamic right-sizing for power-proportional data centers

  • Author

    Lin, Minghong ; Wierman, Adam ; Andrew, Lachlan L H ; Thereska, Eno

  • Author_Institution
    California Inst. of Technol., Pasadena, CA, USA
  • fYear
    2011
  • fDate
    10-15 April 2011
  • Firstpage
    1098
  • Lastpage
    1106
  • Abstract
    Power consumption imposes a significant cost for data centers implementing cloud services, yet much of that power is used to maintain excess service capacity during periods of predictably low load. This paper investigates how much can be saved by dynamically `right-sizing´ the data center by turning off servers during such periods, and how to achieve that saving via an online algorithm. We prove that the optimal offline algorithm for dynamic right-sizing has a simple structure when viewed in reverse time, and this structure is exploited to develop a new `lazy´ online algorithm, which is proven to be 3-competitive. We validate the algorithm using traces from two real data center workloads and show that significant cost-savings are possible.
  • Keywords
    cloud computing; computer centres; power aware computing; power consumption; cloud services; dynamic right-sizing algorithm; lazy online algorithm; power consumption; power-proportional data centers; Data models; Delay; Heuristic algorithms; Optimization; Prediction algorithms; Servers; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    INFOCOM, 2011 Proceedings IEEE
  • Conference_Location
    Shanghai
  • ISSN
    0743-166X
  • Print_ISBN
    978-1-4244-9919-9
  • Type

    conf

  • DOI
    10.1109/INFCOM.2011.5934885
  • Filename
    5934885