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• W2077501147 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 e−x. 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." @default.
• W2077501147 created "2016-06-24" @default.
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• W2077501147 date "1999-02-01" @default.
• W2077501147 modified "2023-10-16" @default.
• W2077501147 title "Sampling at subexponential times, with queueing applications" @default.
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• W2077501147 doi "https://doi.org/10.1016/s0304-4149(98)00064-7" @default.
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