Christoph Lindemann, Axel Thümmler
Performance Evaluation
This paper introduces an efficient numerical algorithm for the steady-state analysis of deterministic and stochastic Petri nets (DSPNs) without structural restrictions on the enabling of deterministic transitions. The method rests on observation, at equidistant time points, of the continuous-time Markov process that records tangible markings of the DSPN and remaining firing times associated with deterministic transitions. This approach results in the analysis of a general state space Markov chain whose system of stationary equations can be transformed into a system of Volterra equations. The techniques of this paper are also applicable to queueing networks, stochastic process algebras, and other discrete-event stochastic systems with an underlying stochastic process which can be represented as a generalized semi-Markov process with exponential and deterministic events.
Christoph Lindemann, Axel Thümmler
Performance Evaluation
Gerald S. Shedler, Jonathan Southard
Performance Evaluation
Donald L. Iglehart, Gerald S. Shedler
WSC 1979
Peter A.W. Lewis, Gerald S. Shedler
WSC 1978