• DocumentCode
    3047167
  • Title

    Adversarial analyses of window backoff strategies

  • Author

    Bender, Michael A. ; Farach-Colton, Martin ; He, Simai ; Kuszmaul, Bradley C. ; Leiserson, Charles E.

  • fYear
    2004
  • fDate
    26-30 April 2004
  • Firstpage
    203
  • Abstract
    Summary form only given. Backoff strategies have typically been analyzed by making statistical assumptions on the distribution of problem inputs. Although these analyses have provided valuable insights into the efficacy of various backoff strategies, they leave open the question as to which backoff algorithms perform best in the worst case or on inputs, such as bursty inputs, that are not covered by the statistical models. We analyze randomized backoff strategies using worst-case assumptions on the inputs.
  • Keywords
    computational complexity; distributed algorithms; multiprogramming; randomised algorithms; backoff algorithm; randomized backoff strategy; statistical assumption; window backoff strategy; worst-case assumption; Algorithm design and analysis; Delay effects; Distributed processing; Feedback; Helium; Laboratories; Partitioning algorithms; Performance analysis; Stability; Throughput;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing Symposium, 2004. Proceedings. 18th International
  • Print_ISBN
    0-7695-2132-0
  • Type

    conf

  • DOI
    10.1109/IPDPS.2004.1303230
  • Filename
    1303230