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Analysis of a large number of Markov chains competing for transitions
Authors:E. Anceaume  F. Castella
Affiliation:1. IRISA/CNRS , Campus de Beaulieu, 35042 Rennes , Cedex , France;2. Campus de Beaulieu , Université de Rennes I, 35042 Rennes , Cedex , France
Abstract:We consider the behaviour of a stochastic system composed of several identically distributed, but non independent, discrete-time absorbing Markov chains competing at each instant for a transition. The competition consists in determining at each instant, using a given probability distribution, the only Markov chain allowed to make a transition. We analyse the first time at which one of the Markov chains reaches its absorbing state. When the number of Markov chains goes to infinity, we analyse the asymptotic behaviour of the system for an arbitrary probability mass function governing the competition. We give conditions that ensure the existence of the asymptotic distribution and we show how these results apply to cluster-based distributed storage when the competition is handled using a geometric distribution.
Keywords:asymptotic analysis  competing Markov chains  cluster-based distributed systems  Markov chains  geometric distribution
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