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Survivors in leader election algorithms
Authors:Ravi Kalpathy  Hosam M Mahmoud  Walter Rosenkrantz
Institution:1. Department of Statistics, The George Washington University, Washington, DC 20052, USA;2. Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, MA 01003, USA
Abstract:We consider the number of survivors in a broad class of fair leader election algorithms after a number of election rounds. We give sufficient conditions for the number of survivors to converge to a product of independent identically distributed random variables. The number of terms in the product is determined by the round number considered. Each individual term in the product is a limit of a scaled random variable associated with the splitting protocol. The proof is established via convergence (to 0) of the first-order Wasserstein distance from the product limit. In a broader context, the paper is a case study of a class of stochastic recursive equations. We give two illustrative examples, one with binomial splitting protocol (for which we show that a normalized version is asymptotically Gaussian) and one with uniform splitting protocol.
Keywords:Randomized algorithm  Leader election  Stochastic recurrence  Probability metrics  Weak convergence
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