NONSTATIONARY LOSS QUEUES VIA CUMULANT MOMENT APPROXIMATIONS

作者:Pender Jamol*
来源:Probability in the Engineering and Informational Sciences, 2015, 29(1): 27-49.
DOI:10.1017/S0269964814000205

摘要

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.

  • 出版日期2015-1