Time warp simulation of stochastic Petri nets

Addresses the problem of developing parallel simulation techniques to analyze complex Stochastic Petri Net (SPN) models. The approach of parallel simulation is to divide a general SPN spatially into several connected subnets. The various subnetworks are simulated in parallel by several logical processes (LPs) which synchronize. The rich and complex structure of Petri Nets necessitates the development of an algorithm which can handle general forms of network partitions. In the paper, an algorithm based on the Time Warp strategy for optimistic parallel simulation is presented. Time scale decomposition is also used with spatial decomposition to induce parallelism and reduce synchronization overhead. An example of performability analysis using both spatial and time-scale decomposition is presented