In: T. Field, P.G. Harrison, J. Bradley, U. Harder (Eds.): Computer Performance Evaluation, Modelling Techniques and Tools 12th International Conference, TOOLS 2002 London, UK, April 14-17, 2002, pages 1-188pp. Springer Verlag, LNCS 2324, April 2002.
Abstract: Generalised Stochastic Petri Nets (GSPNs) suffer from the same problem as any other state-transition modelling technique: it is difficult to represent sufficient states so that general, real life systems can be analysed. In this paper we use symbolic techniques to perform state space exploration for unstructured GSPNs. We present an algorithm for finding an encoding function which attempts to minimize the height of BDDs used to encode GSPN state spaces. This technique brings together and extends a spectrum of ad-hoc heuristics in a formal algorithm. We also develop a BDD state exploration algorithm which incorporates an adjustable memory threshold. Our results show the ability to encode over 108 states using just 13.7MB of memory.