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Iterative Decomposition and Aggregation of Labeled GSPNs

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Book cover Application and Theory of Petri Nets 1998 (ICATPN 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1420))

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Abstract

The use of Stochastic Petri Nets for performance analysis is limited by the state explosion of the underlying Continuous Time Markov Chain. A class of analysis methods to overcome this limitation are based on repeated decomposition and aggregation. In this paper, we propose a general framework for these kinds of solution methods and extend known techniques by introducing new classes of aggregates to reduce the approximation error. Aggregation relies on a formal definition of equivalence of Stochastic Petri Nets, which allows us to build aggregates at several levels of detail. The approach has been completely automated and allows the analysis of large and complex models with a low effort.

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Author information

Authors and Affiliations

  1. Informatik IV, Universität Dortmund, D-44221, Dortmund, Germany

    Peter Buchholz

Authors
  1. Peter Buchholz
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Editor information

Editors and Affiliations

  1. Institut AIFB, University of Karlsruhe, D-76128, Karlsruhe, Germany

    Jörg Desel

  2. Departamento de Informatica a Ingenieria de Sistemas Centro Politecnico Superior, Universidad de Zaragoza, c/ Maria de Luna, 3, E-50015, Zaragoza, Spain

    Manuel Silva

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© 1998 Springer-Verlag Berlin Heidelberg

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Buchholz, P. (1998). Iterative Decomposition and Aggregation of Labeled GSPNs. In: Desel, J., Silva, M. (eds) Application and Theory of Petri Nets 1998. ICATPN 1998. Lecture Notes in Computer Science, vol 1420. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-69108-1_13

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  • DOI: https://doi.org/10.1007/3-540-69108-1_13

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64677-8

  • Online ISBN: 978-3-540-69108-2

  • eBook Packages: Springer Book Archive

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