In: Proc. 8th Int. Workshop on Petri Net and Performance Models (PNPM'99), 8-10 October 1999, Zaragoza, Spain, pages 12-21. IEEE Computer Society Press, 1999.
Abstract: In this paper we present efficient techniques for the generation of very large continuous-time Markov chains (CTMCs) specified as stochastic Petri nets (SPNs). In particular, we investigate how the storage efficiency of the reachability graph generation can be improved by using good state coding techniques and by using hashing tables instead of tree-based data structures. These techniques allow us to analyze SPNs with almost 55 million states on a single workstation. The size of the SPNs that can be handled is then further enlarged by using a cluster of workstations. With 16 workstations, connected via a 100 Mbps Ethernet, we can generate reachability graphs with over 400 million states in reasonable time. The presented techniques have been realized in a prototype tool (PARSECS) implemented in C++ using the libraries STL and MPICH. The SPNs to be input to PARSECS are specified using CSPL, known from the tool SPNP. In the paper we present our techniques and study their performance for a number of case studies. We also present comparisons with SPNP.
Keywords: Markov chains, reachability graphs, stochastic Petri nets, storage techniques.