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Spnps: A Tool for Perfect Sampling in Stochastic Petri Nets

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Quantitative Evaluation of Systems (QEST 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9826))

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Abstract

This paper presents a tool spnps for perfect sampling (PS) in stochastic Petri nets (SPN). SPNs are an important formalism for performance evaluation of telecommunication systems and computer hardware and software architectures. Stochastic process underlying an SPN is a continuous time Markov chain, and the tool obtains samples from this chain, distributed according to its stationary probability distribution. The tool is implemented in C++ and is based on an efficient implementation of coupling from the past, an algorithm for PS in Markov chains. It can be obtained at http://www.dais.unive.it/~stojic/soft.html.

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Notes

  1. 1.

    The GNU General Public License v3.0 - GNU Project - Free Software Foundation, http://www.gnu.org/licenses/gpl-3.0.en.html.

  2. 2.

    Ivan Stojic - software, http://www.dais.unive.it/~stojic/soft.html.

References

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Acknowledgment

Work partially supported by MIUR fund Fondo per il sostegno dei giovani “Programma strategico: ICT e componentistica elettronica”.

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Authors and Affiliations

  1. Università Ca’ Foscari Venezia, DAIS, via Torino 155, Venice, Italy

    Simonetta Balsamo, Andrea Marin & Ivan Stojic

Authors
  1. Simonetta Balsamo
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  2. Andrea Marin
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  3. Ivan Stojic
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Corresponding author

Correspondence to Simonetta Balsamo .

Editor information

Editors and Affiliations

  1. University of Illinois , Urbana, Illinois, USA

    Gul Agha

  2. University of Antwerp , Antwerp, Belgium

    Benny Van Houdt

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Balsamo, S., Marin, A., Stojic, I. (2016). Spnps: A Tool for Perfect Sampling in Stochastic Petri Nets. In: Agha, G., Van Houdt, B. (eds) Quantitative Evaluation of Systems. QEST 2016. Lecture Notes in Computer Science(), vol 9826. Springer, Cham. https://doi.org/10.1007/978-3-319-43425-4_11

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  • DOI: https://doi.org/10.1007/978-3-319-43425-4_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43424-7

  • Online ISBN: 978-3-319-43425-4

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