Automated rare event simulation for stochastic Petri nets

D.P. Reijsbergen, Pieter-Tjerk de Boer, Willem R.W. Scheinhardt, Boudewijn R.H.M. Haverkort, K. Joshi (Editor), M. Siegle, M. Stoelinga, P.R. d' Argenio (Editor)

Research output: Other contributionOther research output

Abstract

We introduce an automated approach for applying rare event simulation to stochastic Petri net (SPN) models of highly reliable systems. Rare event simulation can be much faster than standard simulation because it is able to exploit information about the typical behaviour of the system. Previously, such information came from heuristics, human insight, or analysis on the full state space. We present a formal algorithm that obtains the required information from the high-level SPN- description, without generating the full state space. Essentially, our algorithm reduces the state space of the model into a (much smaller) graph in which each node represents a set of states for which the most likely path to failure has the same form. We empirically demonstrate the efficiency of the method with two case studies.
Original languageEnglish
PublisherSpringer
Number of pages17
Place of PublicationBerlin, Heidelberg
ISBN (Print)978-3-642-40195-4
DOIs
Publication statusPublished - 2013
Externally publishedYes

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Petri nets

Keywords

  • EWI-23929
  • IR-87777
  • METIS-300136

Cite this

Reijsbergen, D. P., de Boer, P-T., Scheinhardt, W. R. W., Haverkort, B. R. H. M., Joshi, K. (Ed.), Siegle, M., ... d' Argenio, P. R. (Ed.) (2013). Automated rare event simulation for stochastic Petri nets. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-40196-1
Reijsbergen, D.P. ; de Boer, Pieter-Tjerk ; Scheinhardt, Willem R.W. ; Haverkort, Boudewijn R.H.M. ; Joshi, K. (Editor) ; Siegle, M. ; Stoelinga, M. ; d' Argenio, P.R. (Editor). / Automated rare event simulation for stochastic Petri nets. 2013. Berlin, Heidelberg : Springer. 17 p.
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abstract = "We introduce an automated approach for applying rare event simulation to stochastic Petri net (SPN) models of highly reliable systems. Rare event simulation can be much faster than standard simulation because it is able to exploit information about the typical behaviour of the system. Previously, such information came from heuristics, human insight, or analysis on the full state space. We present a formal algorithm that obtains the required information from the high-level SPN- description, without generating the full state space. Essentially, our algorithm reduces the state space of the model into a (much smaller) graph in which each node represents a set of states for which the most likely path to failure has the same form. We empirically demonstrate the efficiency of the method with two case studies.",
keywords = "EWI-23929, IR-87777, METIS-300136",
author = "D.P. Reijsbergen and {de Boer}, Pieter-Tjerk and Scheinhardt, {Willem R.W.} and Haverkort, {Boudewijn R.H.M.} and K. Joshi and M. Siegle and M. Stoelinga and {d' Argenio}, P.R.",
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Reijsbergen, DP, de Boer, P-T, Scheinhardt, WRW, Haverkort, BRHM, Joshi, K (ed.), Siegle, M, Stoelinga, M & d' Argenio, PR (ed.) 2013, Automated rare event simulation for stochastic Petri nets. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40196-1

Automated rare event simulation for stochastic Petri nets. / Reijsbergen, D.P.; de Boer, Pieter-Tjerk; Scheinhardt, Willem R.W.; Haverkort, Boudewijn R.H.M.; Joshi, K. (Editor); Siegle, M.; Stoelinga, M.; d' Argenio, P.R. (Editor).

17 p. Berlin, Heidelberg : Springer. 2013, .

Research output: Other contributionOther research output

TY - GEN

T1 - Automated rare event simulation for stochastic Petri nets

AU - Reijsbergen, D.P.

AU - de Boer, Pieter-Tjerk

AU - Scheinhardt, Willem R.W.

AU - Haverkort, Boudewijn R.H.M.

AU - Siegle, M.

AU - Stoelinga, M.

A2 - Joshi, K.

A2 - d' Argenio, P.R.

N1 - 10.1007/978-3-642-40196-1

PY - 2013

Y1 - 2013

N2 - We introduce an automated approach for applying rare event simulation to stochastic Petri net (SPN) models of highly reliable systems. Rare event simulation can be much faster than standard simulation because it is able to exploit information about the typical behaviour of the system. Previously, such information came from heuristics, human insight, or analysis on the full state space. We present a formal algorithm that obtains the required information from the high-level SPN- description, without generating the full state space. Essentially, our algorithm reduces the state space of the model into a (much smaller) graph in which each node represents a set of states for which the most likely path to failure has the same form. We empirically demonstrate the efficiency of the method with two case studies.

AB - We introduce an automated approach for applying rare event simulation to stochastic Petri net (SPN) models of highly reliable systems. Rare event simulation can be much faster than standard simulation because it is able to exploit information about the typical behaviour of the system. Previously, such information came from heuristics, human insight, or analysis on the full state space. We present a formal algorithm that obtains the required information from the high-level SPN- description, without generating the full state space. Essentially, our algorithm reduces the state space of the model into a (much smaller) graph in which each node represents a set of states for which the most likely path to failure has the same form. We empirically demonstrate the efficiency of the method with two case studies.

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KW - IR-87777

KW - METIS-300136

U2 - 10.1007/978-3-642-40196-1

DO - 10.1007/978-3-642-40196-1

M3 - Other contribution

SN - 978-3-642-40195-4

PB - Springer

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ER -

Reijsbergen DP, de Boer P-T, Scheinhardt WRW, Haverkort BRHM, Joshi K, (ed.), Siegle M et al. Automated rare event simulation for stochastic Petri nets. 2013. 17 p. https://doi.org/10.1007/978-3-642-40196-1