Workshop on Stochasticity in Distributed Systems

Research Article

Stochasticity of probabilistic systems: analysis methodologies case-study

  • @INPROCEEDINGS{10.1109/COLCOM.2005.1651267,
        author={Anwitaman Datta and Martin Hasler and Karl Aberer},
        title={Stochasticity of probabilistic systems: analysis methodologies case-study},
        proceedings={Workshop on Stochasticity in Distributed Systems},
        keywords={Algorithm design and analysis  Distributed computing  Distribution functions  Equations  Information analysis  Large-scale systems  Probability distribution  Steady-state  Stochastic processes  Stochastic systems},
  • Anwitaman Datta
    Martin Hasler
    Karl Aberer
    Year: 2006
    Stochasticity of probabilistic systems: analysis methodologies case-study
    DOI: 10.1109/COLCOM.2005.1651267
Anwitaman Datta1,*, Martin Hasler1,*, Karl Aberer1,*
  • 1: Ecole Polytechnique Fédérale de Lausanne (EPFL), School of Computer and Communication Sciences, CH-1015 Lausanne, Switzerland
*Contact email:,,


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).