Long Term Dependences and Heavy Tails in Traffics and Queues Generated by Memoriless on/off Sources in Series

Philippe Jacquet 1
1 HIPERCOM - High performance communication
Inria Paris-Rocquencourt, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, X - École polytechnique, CNRS - Centre National de la Recherche Scientifique : UMR
Abstract : This repport presents the analytical study of a surprising case where a denumerable set of independent and memoriless on/off sources in series creates a traffic with long term dependences. We use Mellin transform to characterize the asymptotic behavior of those dependences. We use similar tools to analyse the queue size of a server subject to these sources in series. This architecture roughly models a shared network like internet. We show that the queue size distribution has a heavy tail. These results agree with the recent experimental datas collected on Web activity.
Type de document :
Rapport
[Research Report] RR-3516, INRIA. 1998
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https://hal.inria.fr/inria-00073168
Contributeur : Rapport de Recherche Inria <>
Soumis le : mercredi 24 mai 2006 - 12:02:25
Dernière modification le : mardi 17 avril 2018 - 11:33:36
Document(s) archivé(s) le : dimanche 4 avril 2010 - 23:36:49

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Philippe Jacquet. Long Term Dependences and Heavy Tails in Traffics and Queues Generated by Memoriless on/off Sources in Series. [Research Report] RR-3516, INRIA. 1998. 〈inria-00073168〉

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