In: IEEE Transactions on Software Engineering, Volume 20, Issue 7, pages 506-515. IEEE Press, July 1994.
Abstract: Stochastic Petri nets (SPN's) with generally distributed firing times can model a large class of systems, but simulation is the only feasible approach for their solution. We explore a hierarchy of SPN classes where modeling power is reduced in exchange for an increasingly efficient solution. Generalized stochastic Petri nets (GSPN's), deterministic and stochastic Petri nets (DSPN's), semi-Markovian stochastic Petri nets (SM-SPN's), timed Petri nets (TPN's), and generalized timed Petri nets (GTPN's) are particular entries in our hierarchy. Additional classes of SPN's for which we show how to compute an analytical solution are obtained by the method of the embedded Markov chain (DSPN's are just one example in this class) and state discretization, which we apply not only to the continuous-time case (PH-type distributions), but also to the discrete case.
Keywords: Markov processes; PH-type distributions; Petri nets; SPN classes; continuous-time case; deterministic Petri nets; distributed firing times; embedded Markov chain; generalized stochastic Petri nets; generalized timed Petri nets; modeling power; semiMarkovian stochastic Petri nets; simulation; state discretization; stochastic Petri net; stochastic Petri nets; stochastic process; stochastic processes; timed Petri nets.
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