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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Gaeta, R. Chiola, G. |
| Copyright Year | 1995 |
| Description | Author affiliation: Dipartimento di Inf., Torino Univ., Italy (Gaeta, R.) |
| Abstract | Coloured Petri nets are a powerful formalism for the description of complex, asynchronous distributed systems. They can express in a very concise way the behaviour of very large system especially in case these systems are composed of many replications of a few basic components that individually behave in a similar way. The simulation of such models is however difficult to perform in a computationally efficient way. For the specific class of well formed stochastic nets (SWN) we present a set of techniques that allow a very efficient implementation of the event-driven simulation approach. Two approaches are followed to improve simulation efficiency: first, reduction of the amount of work needed to schedule or preempt the occurrence of a transition as a consequence of a marking change, taking into account the restrictions on colour functions for the WN formalism; second, reduction of the average length of the event list in the case of symmetric models where the so called symbolic simulation technique applies. The approach is validated by performance measurements on several large SWN models taken from the literature. |
| Starting Page | 137 |
| Ending Page | 146 |
| File Size | 1046380 |
| Page Count | 10 |
| File Format | |
| ISBN | 0818672102 |
| ISSN | 10636714 |
| DOI | 10.1109/PNPM.1995.524324 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1995-10-03 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Discrete event simulation Engines Computational modeling Petri nets Stochastic processes Partitioning algorithms Parallel machines Virtual prototyping Distributed algorithms Parallel architectures |
| Content Type | Text |
| Resource Type | Article |
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