A method to abstract a stochastic Petri net

We propose a method to abstract a given stochastic Petri net (SPN). We shall show that the reachability tree of the given SPN is isomorphic to a Markov renewal process. Then, the given SPN is transformed to a state transition system (STS) and the STS is reduced. The reduction of states on STS corresponds to a fusion of series transitions on the SPN. The reduced STS is again transformed to an abstract SPN. We show that it is helpful to use the notion of the conditional firstpassage time from a certain state to the others on the STS to reduce nonessential states, thus places and transitions on the given SPN. Mass functions, that is, the distribution functions of conditional first-passage time between preserved states on the reduced MRP, preserve firing probabilities of fused transitions. Firing probability of the preserved transition also preserves the stochastic properties of the fused transitions.