• DocumentCode
    2213350
  • Title

    Stochasticity of probabilistic systems: analysis methodologies case-study

  • Author

    Datta, Anwitaman ; Hasler, Martin ; Aberer, Karl

  • Author_Institution
    Sch. of Comput. & Commun. Sci., Ecole Polytechnique Federale de Lausanne
  • fYear
    0
  • fDate
    0-0 0
  • Abstract
    We do a case study of two different analysis techniques for studying the stochastic behavior of a randomized system/algorithms: (i) The first approach can be broadly termed as a mean value analysis (MVA), where the evolution of the mean state is studied assuming that the system always actually resides in the mean state; (ii) The second approach looks at the probability distribution function of the system states at any time instance, thus studying the evolution of the (probability mass) distribution function (EoDF)
  • Keywords
    statistical distributions; stochastic processes; mean value analysis; probabilistic system stochasticity; probability distribution function; randomized algorithms; randomized system; stochastic behavior; Algorithm design and analysis; Distributed computing; Distribution functions; Equations; Information analysis; Large-scale systems; Probability distribution; Steady-state; Stochastic processes; Stochastic systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Collaborative Computing: Networking, Applications and Worksharing, 2005 International Conference on
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    1-4244-0030-9
  • Type

    conf

  • DOI
    10.1109/COLCOM.2005.1651267
  • Filename
    1651267