Techniques for simulating difficutl queueing problems: adaptive importance sampling simulation of queueing networks

Authors:
Pieter-Tjerk de Boer;Victor F. Nicola;Reuven Y. Rubinstein
Affiliations:
University of Twente, 7500 AE Enschede, The Netherlands;University of Twente, 7500 AE Enschede, The Netherlands;Technion, Haifa, Israel
Venue:
Proceedings of the 32nd conference on Winter simulation
Year:
2000

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Abstract

In this paper, a method is presented for the efficient estimation of rare-event (overflow) probabilities in Jackson queueing networks using importance sampling. The method differs in two ways from methods discussed in most earlier literature: the change of measure is state-dependent, i.e., it is a function of the content of the buffers, and the change of measure is determined using a cross-entropy-based adaptive procedure. This method yields asymptotically efficient estimation of overflow probabilities of queueing models for which it has been shown that methods using a state-independent change of measure are not asymptotically efficient. Numerical results demonstrating the effectiveness of the method are presented as well.