Volume 134, Number 1, 69-100, DOI: 10.1007/s10479-005-5725-y

Rare-Event Simulation of Non-Markovian Queueing Networks Using a State-Dependent Change of Measure Determined Using Cross-Entropy

Pieter-Tjerk de Boer

From the issue entitled "The Cross-Entropy Method for Combinatorial Optimization, Rare Event Simulation and Neural Computation"

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Abstract

A method is described for the efficient estimation of small overflow probabilities in nonMarkovian queueing network models. The method uses importance sampling with a state-dependent change of measure, which is determined adaptively using the cross-entropy method, thus avoiding the need for a detailed mathematical analysis. Experiments show that the use of rescheduling is needed in order to get a significant simulation speedup, and that the method can be used to estimate overflow probabilities in a two-node tandem queue network model for which simulation using a state-independent change of measure does not work well.

Key words  cross-entropy method - rare-event simulation - queueing networks

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