Analysis and Evaluation of Non-Markovian Stochastic Petri Nets

  • András Horváth
  • Antonio Puliafito
  • Marco Scarpa
  • Miklós Telek
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1786)


In order to extend their applicability to more complex situations, in this paper we present a new approach for the analysis of non-Markovian Stochastic Petri Net (NMSPN) models, which is based on a discrete time approximation of the stochastic behavior of the marking process. The proposed approach, which resulted in a new modeling tool for the analysis of NMSPNs called WebSPN, allows to analyze a wider class of PN models with prd, prs and pri concurrently enabled generally distributed transitions. This implies the possibility of dealing with very complex systems with arbitrarily distributed events with very complex interrelations among each other. The adopted technique is described, an application example is solved and the results are carefully analyzed in order to demonstrate the validity of the proposed approach.


Time Slot Stochastic Behavior Discrete Time Markov Chain Reachability Graph Discrete Time Approximation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • András Horváth
    • 1
  • Antonio Puliafito
    • 2
  • Marco Scarpa
    • 2
  • Miklós Telek
    • 1
  1. 1.Department of TelecommunicationsTechnical University of BudapestBudapestHungary
  2. 2.Istituto di Informatica e TelecomunicazioniUniversità di CataniaCataniaItaly

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