Ascending runs in dependent uniformly distributed random variables: Application to wireless networks

Nathalie Mitton 1 Katy Paroux 2 Bruno Sericola 3 Sébastien Tixeuil 4
1 POPS - System and Networking for Portable Objects Proved to be Safe
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe, IRCICA
3 DIONYSOS - Dependability Interoperability and perfOrmance aNalYsiS Of networkS
Inria Rennes – Bretagne Atlantique , IRISA-D2 - RÉSEAUX, TÉLÉCOMMUNICATION ET SERVICES
4 GRAND-LARGE - Global parallel and distributed computing
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LIFL - Laboratoire d'Informatique Fondamentale de Lille, LRI - Laboratoire de Recherche en Informatique
Abstract : We analyze in this paper the longest increasing contiguous sequence or maximal ascending run of random variables with common uniform distribution but not independent. Their dependence is characterized by the fact that two successive random variables cannot take the same value. Using a Markov chain approach, we study the distribution of the maximal ascending run and we develop an algorithm to compute it. This problem comes from the analysis of several self-organizing protocols designed for large-scale wireless sensor networks, and we show how our results apply to this domain.
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https://hal.inria.fr/inria-00239348
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Submitted on : Monday, February 25, 2008 - 10:04:31 AM
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  • HAL Id : inria-00239348, version 5
  • ARXIV : 0802.1387

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Nathalie Mitton, Katy Paroux, Bruno Sericola, Sébastien Tixeuil. Ascending runs in dependent uniformly distributed random variables: Application to wireless networks. [Research Report] RR-6443, INRIA. 2008, pp.12. ⟨inria-00239348v5⟩

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