Sampling at subexponential times, with queueing applications

Søren Asmussen, Claudia Klüppelberg and Karl Sigman

Stochastic Processes and their Applications, 1999, vol. 79, issue 2, 265-286

Abstract: We study the tail asymptotics of the r.v. X(T) where {X(t)} is a stochastic process with a linear drift and satisfying some regularity conditions like a central limit theorem and a large deviations principle, and T is an independent r.v. with a subexponential distribution. We find that the tail of X(T) is sensitive to whether or not T has a heavier or lighter tail than a Weibull distribution with tail . This leads to two distinct cases, heavy tailed and moderately heavy tailed, but also some results for the classical light-tailed case are given. The results are applied via distributional Little's law to establish tail asymptotics for steady-state queue length in GI/GI/1 queues with subexponential service times. Further applications are given for queues with vacations, and M/G/1 busy periods.

Keywords: Busy; period; Independent; sampling; Laplace's; method; Large; deviations; Little's; law; Markov; additive; process; Poisson; process; Random; walk; Regular; variation; Subexponential; distribution; Vacation; model; Weibull; distribution (search for similar items in EconPapers)
Date: 1999
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Citations: View citations in EconPapers (14)

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