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
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