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Iterative Analysis of Markov Regenerative Models

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Computer Performance Evaluation.Modelling Techniques and Tools (TOOLS 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1786))

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Abstract

Conventional algorithms for the steady-state analysis of Markov regenerative models suffer from high computational costs which are caused by densely populated matrices. In this paper a new algorithm is suggested which avoids to compute these matrices explicitly. Instead, a two-stage iteration scheme is used. An extended version of uniformization is applied as a subalgorithm to compute the required transient quantities “on-the fly”. The algorithm is formulated in terms of stochastic Petri nets. A detailed example illustrates the proposed concepts.

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Author information

Authors and Affiliations

  1. Prozeßdatenverarbeitung und Robotik, Technische Universität Berlin, Franklinstr. 28/29, 10587, Berlin, Germany

    Reinhard German

Authors
  1. Reinhard German
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Editor information

Editors and Affiliations

  1. Department of Computer Science, RWTH Aachen, 52056, Aachen, Germany

    Boudewijn R. Haverkort  & Henrik C. Bohnenkamp  & 

  2. Performance Engineering Services Division, MS 110, L&S Computer Technology, Inc., P.O. Box 9802, Austin, TX, 78766, USA

    Connie U. Smith

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© 2000 Springer-Verlag Berlin Heidelberg

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German, R. (2000). Iterative Analysis of Markov Regenerative Models. In: Haverkort, B.R., Bohnenkamp, H.C., Smith, C.U. (eds) Computer Performance Evaluation.Modelling Techniques and Tools. TOOLS 2000. Lecture Notes in Computer Science, vol 1786. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46429-8_12

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  • DOI: https://doi.org/10.1007/3-540-46429-8_12

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67260-9

  • Online ISBN: 978-3-540-46429-7

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