In this paper, we proposed reduction operators of timed Petri net for efficient model checking. Timed Petri nets are used widely for modeling and analyzing systems which include time concept. Analysis of the system can be done comprehensively with model checking, but there is a state-space explosion problem. Therefore, previous researchers proposed reduction methods and translation methods to timed automata to perform efficient model checking. However, there is no reduction method which consider observability and there is a trade-off between the amount of description and the size of state space. In this paper, first, we have defined a concept of timed behavioral inheritance. Next, we have proposed reduction operators of timed Petri nets based on timed behavioral inheritance. Then, we have applied our proposed operators to an artificial timed Petri net. Moreover, the results show that the reduction operators which consider observability can reduce the size of state space of the original timed Petri nets within the experiment.

There are various existing methods translating timed Petri nets to timed automata. However, there is a trade-off between the amount of description and the size of state space. The amount of description and the size of state space affect the feasibility of modeling and analysis like model checking. In this paper, we propose a new translation method from timed Petri nets to timed automata. Our method translates from a timed Petri net to an automaton with the following features: (i) The number of location is 1; (ii) Each edge represents the firing of transition; (iii) Each state implemented as clocks and variables represents a state of the timed Petri net one-to-one correspondingly. Through these features, the amount of description is linear order and the size of state space is the same order as that of the Petri net. We applied our method to three Petri net models of signaling pathways and compared our method with existing methods from the view points of the amount of description and the size of state space. And the comparison results show that our method keeps a good balance between the amount of description and the size of state space. These results also show that our method is effective when checking properties of timed Petri nets.