Sample path large deviation principles for Poisson shot noise processes, and applications

AJ Ganesh, C Macci, GL Torrisi

Research output: Contribution to journalArticle (Academic Journal)peer-review

16 Citations (Scopus)

Abstract

This paper concerns sample path large deviations for Poisson shot noise processes, and applications in queueing theory. We first show that, under an exponential tail condition, Poisson shot noise processes satisfy a sample path large deviations principle with respect to the topology of pointwise convergence. Under a stronger superexponential tail condition, we extend this result to the topology of uniform convergence. We also give applications of this result to determining the most likely path to overflow in a single server queue, and to finding tail asymptotics for the queue lengths at priority queues.
Translated title of the contributionSample path large deviation principles for Poisson shot noise processes, and applications
Original languageEnglish
Pages (from-to)1026 - 1043
Number of pages18
JournalElectronic Journal of Probability
Volume10
Publication statusPublished - Aug 2005

Bibliographical note

Publisher: Univ Washington, Dept of Mathematics

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