State-space Construction of Hybrid Petri Nets with Multiple Stochastic Firings

Abstract

Hybrid Petri nets have been extended to include general transitions that fire after a randomly distributed amount of time. With a single general one-shot transition the state space and evolution over time can be represented either as a Parametric Location Tree or as a Stochastic Time Diagram . Recent work has shown that both representations can be combined and then allow multiple stochastic firings. This work presents an algorithm for building the Parametric Location Tree with multiple general transition firings and shows how its transient probability distribution can be computed using multi-dimensional integration. We discuss the (dis-)advantages of an interval arithmetic and a geometric approach to compute the areas of integration. Furthermore, we provide details on how to perform a Monte Carlo integration either directly on these intervals or convex polytopes, or after transformation to standard simplices. A case study on a battery-backup system shows the feasibility of the approach and discusses the performance of the different integration approaches.

ARCH-COMP23 Category Report: Stochastic Models

“…Monte Carlo integration algorithms for multi-dimensional integration are provided by the GNU Scientific Library (GSL) [4] and improved for high-dimensional polytopes [28]. RealySt builds on the tool hpnmg [9], a model checker for Hybrid Petri nets with an arbitrary but finite number of general transition firings for specifications formulated in STL [10,12,13,11] and on the flowpipe-based approach to optimize reachability probabilities in singular automata with random clocks [23]. RealySt is currently being developed within the DFG project 471367371 as a cooperation between the RWTH Aachen and the University of Münster and is available at https://zivgitlab.uni-muenster.de/ag-sks/tools/realyst.…”