Dynamic interaction graphs with probabilistic edge decay
Wenlei Xie, Yuanyuan Tian, et al.
ICDE 2015
Generalized semi-Markov processes and stochastic Petri nets provide building blocks for specification of discrete event system simulations on a finite or countable state space. The two formal systems differ, however, in the event scheduling (clock-setting) mechanism, the state transition mechanism, and the form of the state space. We have shown previously that stochastic Petri nets have at least the modeling power of generalized semi-Markov processes. In this paper we show that stochastic Petri nets and generalized semi-Markov processes, in fact, have the same modeling power. Combining this result with known results for generalized semi-Markov processes, we also obtain conditions for time-average convergence and convergence in distribution along with a central limit theorem for the marking process of a stochastic Petri net. © 1991, Cambridge University Press. All rights reserved.
Wenlei Xie, Yuanyuan Tian, et al.
ICDE 2015
Bum Chul Kwon, Janu Verma, et al.
IEE CG&A
Donald L. Iglehart, Gerald S. Shedler
Acta Informatica
Peter J. Haas, Jeffrey F. Naughton, et al.
Journal of Computer and System Sciences