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NONSTATIONARY LOSS QUEUES VIA CUMULANT MOMENT APPROXIMATIONS

Published online by Cambridge University Press:  15 September 2014

Jamol Pender*
Affiliation:
School of Operations Research and Information Engineering, Cornell University, Ithaca, NY 14850, USA E-mail: jjp274@cornell.edu

Abstract

In this paper, we provide a new technique for analyzing the nonstationary Erlang loss queueing model with abandonment. Our method uniquely combines the use of the functional Kolmogorov forward equations with the well-known Gram-Charlier series expansion from the statistics literature. Using the Gram-Charlier series expansion, we show that we can estimate salient performance measures of the loss queue such as the mean, variance, skewness, kurtosis, and blocking probability. Lastly, we provide numerical examples to illustrate the effectiveness of our approximations.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2014 

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