Rare-event simulation of non-Markovian queueing networks using a state-dependent change of measure determined using cross-entropy

Pieter-Tjerk de Boer

Rare-event simulation of non-Markovian queueing networks using a state-dependent change of measure determined using cross-entropy

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Abstract

A method is described for the efficient estimation of small overflow probabilities in non-Markovian 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 of the model. Experiments show 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.

Original language	English
Pages	1-6
Number of pages	6
Publication status	Published - 7 Sept 2004
Event	5th International Workshop on Rare Event Simulation and Combinatorial Optimization, RESIM/COP 2004 - Budapest, Hungary Duration: 7 Sept 2004 → 8 Sept 2004 Conference number: 5

Conference

Conference	5th International Workshop on Rare Event Simulation and Combinatorial Optimization, RESIM/COP 2004
Abbreviated title	RESIM/COP
Country/Territory	Hungary
City	Budapest
Period	7/09/04 → 8/09/04

Keywords

Cross-entropy method
Rare-event simulation
Queueing networks

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title = "Rare-event simulation of non-Markovian queueing networks using a state-dependent change of measure determined using cross-entropy",

abstract = "A method is described for the efficient estimation of small overflow probabilities in non-Markovian 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 of the model. Experiments show 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.",

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N2 - A method is described for the efficient estimation of small overflow probabilities in non-Markovian 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 of the model. Experiments show 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.

AB - A method is described for the efficient estimation of small overflow probabilities in non-Markovian 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 of the model. Experiments show 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.

KW - Cross-entropy method

KW - Rare-event simulation

KW - Queueing networks

M3 - Paper

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T2 - 5th International Workshop on Rare Event Simulation and Combinatorial Optimization, RESIM/COP 2004

Y2 - 7 September 2004 through 8 September 2004

ER -

Rare-event simulation of non-Markovian queueing networks using a state-dependent change of measure determined using cross-entropy

Abstract

Conference

Keywords

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