• DocumentCode
    2304305
  • Title

    Energy optimization policies for server clusters

  • Author

    Singh, Nidhi ; Rao, Shrisha

  • Author_Institution
    IBM India Private Ltd., India
  • fYear
    2010
  • fDate
    21-24 Aug. 2010
  • Firstpage
    293
  • Lastpage
    300
  • Abstract
    We construct energy optimization policies for a server cluster, using statistical data analyses and demand prediction methodologies, with an aim to reduce the power consumption of the server cluster. In doing so, we monitor and analyze the historical time-series utilization data of a server cluster. Based on the analyses results, we develop predictions about utilization of servers for future time periods. Using this predictive analysis, we formulate energy optimization rules or policies for the server cluster. These policies are then evaluated to determine if they result in energy savings in the server cluster. High-level implementation of this entire mechanism is provided and a strategy for inclusion of this mechanism in existing data center automation products is discussed.
  • Keywords
    power aware computing; statistical analysis; time series; data center automation product; energy optimization policy; power consumption; predictive analysis; server cluster; statistical data analysis; time-series utilization data; Automation; Data analysis; Monitoring; Optimization; Power demand; Resource management; Servers; data center automation; energy optimization; policy creation; server clusters; workload prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation Science and Engineering (CASE), 2010 IEEE Conference on
  • Conference_Location
    Toronto, ON
  • Print_ISBN
    978-1-4244-5447-1
  • Type

    conf

  • DOI
    10.1109/COASE.2010.5584153
  • Filename
    5584153