Discrete - Time Markovianstochastic Petri

We revisit and extend the original deenition of discrete-time stochastic Petri nets, by allowing the ring times to have a \defective discrete phase distribution". We show that this formalism still corresponds to an underlying discrete-time Markov chain. The structure of the state for this process describes both the marking of the Petri net and the phase of the ring time for of each transition, resulting in a large state space. We then modify the well-known power method to perform a transient analysis even when the state space is innnite, subject to the condition that only a nite number of states can be reached in a nite amount of time. Since the memory requirements might still be excessive, we suggest a bounding technique based on truncation.