• DocumentCode
    2887654
  • Title

    Online dynamic capacity provisioning in data centers

  • Author

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

  • fYear
    2011
  • fDate
    28-30 Sept. 2011
  • Firstpage
    1159
  • Lastpage
    1163
  • Abstract
    Power consumption imposes a significant cost for implementing cloud services, yet much of that power is used to maintain excess service capacity during periods of low load. In this work, we study how to avoid such waste via an on-line dynamic capacity provisioning. We overview recent results showing that the optimal offline algorithm for dynamic capacity provisioning has a simple structure when viewed in reverse time, and this structure can be exploited to develop a new ´lazy´ online algorithm which is 3-competitive. Additionally, we analyze the performance of the more traditional approach of receding horizon control and introduce a new variant with a significantly improved worst-case performance guarantee.
  • Keywords
    cloud computing; computer centres; power aware computing; power consumption; cloud service; data centers; excess service capacity; lazy online algorithm; low load; online dynamic capacity provisioning; power consumption; receding horizon control approach; service capacity; worst-case performance guarantee; Delay; Heuristic algorithms; Optimization; Prediction algorithms; Servers; Switches; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication, Control, and Computing (Allerton), 2011 49th Annual Allerton Conference on
  • Conference_Location
    Monticello, IL
  • Print_ISBN
    978-1-4577-1817-5
  • Type

    conf

  • DOI
    10.1109/Allerton.2011.6120298
  • Filename
    6120298