• DocumentCode
    2947657
  • Title

    Stochastic analysis of power-aware scheduling

  • Author

    Wierman, Adam ; Andrew, Lachlan L H ; Tang, Ao

  • Author_Institution
    Comput. Sci. Dept., California Inst. of Technol., Pasadena, CA
  • fYear
    2008
  • fDate
    23-26 Sept. 2008
  • Firstpage
    1278
  • Lastpage
    1283
  • Abstract
    Energy consumption in a computer system can be reduced by dynamic speed scaling, which adapts the processing speed to the current load. This paper studies the optimal way to adjust speed to balance mean response time and mean energy consumption, when jobs arrive as a Poisson process and processor sharing scheduling is used. Both bounds and asymptotics for the optimal speeds are provided. Interestingly, a simple scheme that halts when the system is idle and uses a static rate while the system is busy provides nearly the same performance as the optimal dynamic speed scaling. However, dynamic speed scaling which allocates a higher speed when more jobs are present significantly improves robustness to bursty traffic and mis-estimation of workload parameters.
  • Keywords
    Internet; energy consumption; power aware computing; processor scheduling; stochastic processes; Poisson process; dynamic speed scaling; energy consumption; mean energy consumption; mean response time; power-aware scheduling; processor sharing; stochastic analysis; Computer science; Costs; Delay; Energy consumption; Internet; Measurement; Power system modeling; Processor scheduling; Robustness; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication, Control, and Computing, 2008 46th Annual Allerton Conference on
  • Conference_Location
    Urbana-Champaign, IL
  • Print_ISBN
    978-1-4244-2925-7
  • Electronic_ISBN
    978-1-4244-2926-4
  • Type

    conf

  • DOI
    10.1109/ALLERTON.2008.4797707
  • Filename
    4797707