A Fixed-Point Algorithm for Closed Queueing Networks

R. Sadre, Boudewijn R.H.M. Haverkort, Patrick Reinelt, K. Wolter

Research output: Other contribution

Abstract

In this paper we propose a new efficient iterative scheme for solving closed queueing networks with phase-type service time distributions. The method is especially efficient and accurate in case of large numbers of nodes and large customer populations. We present the method, put it in perspective, and validate it through a large number of test scenarios. In most cases, the method provides accuracies within 5% relative error (in comparison to discrete-event simulation).
Original languageEnglish
PublisherSpringer
Number of pages17
ISBN (Print)978-3-540-75210-3
DOIs
Publication statusPublished - 2007
Externally publishedYes

Fingerprint

Queueing networks
Discrete event simulation

Keywords

  • IR-64424
  • METIS-242205
  • EWI-11260

Cite this

Sadre, R. ; Haverkort, Boudewijn R.H.M. ; Reinelt, Patrick ; Wolter, K. / A Fixed-Point Algorithm for Closed Queueing Networks. 2007. Springer. 17 p.
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A Fixed-Point Algorithm for Closed Queueing Networks. / Sadre, R.; Haverkort, Boudewijn R.H.M.; Reinelt, Patrick; Wolter, K.

17 p. Springer. 2007, .

Research output: Other contribution

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AU - Haverkort, Boudewijn R.H.M.

AU - Reinelt, Patrick

AU - Wolter, K.

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PY - 2007

Y1 - 2007

N2 - In this paper we propose a new efficient iterative scheme for solving closed queueing networks with phase-type service time distributions. The method is especially efficient and accurate in case of large numbers of nodes and large customer populations. We present the method, put it in perspective, and validate it through a large number of test scenarios. In most cases, the method provides accuracies within 5% relative error (in comparison to discrete-event simulation).

AB - In this paper we propose a new efficient iterative scheme for solving closed queueing networks with phase-type service time distributions. The method is especially efficient and accurate in case of large numbers of nodes and large customer populations. We present the method, put it in perspective, and validate it through a large number of test scenarios. In most cases, the method provides accuracies within 5% relative error (in comparison to discrete-event simulation).

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KW - EWI-11260

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