Simple and fast approximations for generalized stochastic Petri nets
A primary problem with generalized stochastic Petri nets (GSPNs) is the exponential explosion in the number of reachable states. This limits the GSPN modeling capability. We present an algorithm that circumvents the problem by not enumerating the entire state space to find a solution. Instead, it co...
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| Veröffentlicht in: | The Journal of systems and software 1993-05, Vol.21 (2), p.163-177 |
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| container_title | The Journal of systems and software |
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| creator | von Mayrhauser, A. Dube, Deepak |
| description | A primary problem with generalized stochastic Petri nets (GSPNs) is the exponential explosion in the number of reachable states. This limits the GSPN modeling capability. We present an algorithm that circumvents the problem by not enumerating the entire state space to find a solution. Instead, it considers token flow balance and the preferred cycle heuristic to reduce the number of reachable states by an order of magnitude. This provides fast approximations of performance measures of systems modeled as GSPNs. Comparisons show how accurate the approximations are. We also give criteria that help system modelers ensure high approximation accuracy. |
| doi_str_mv | 10.1016/0164-1212(93)90039-Z |
| format | Article |
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| ispartof | The Journal of systems and software, 1993-05, Vol.21 (2), p.163-177 |
| issn | 0164-1212 1873-1228 |
| language | eng |
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| source | Elsevier ScienceDirect Journals Complete |
| subjects | Algorithms Applied sciences Approximation Computer programming Computer science control theory systems Control theory. Systems Exact sciences and technology Modelling and identification Stochastic models Studies Systems development |
| title | Simple and fast approximations for generalized stochastic Petri nets |
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