Region-Based Analysis of Hybrid Petri Nets with a Single General One-Shot Transition
- 439 Downloads
Recently, hybrid Petri nets with a single general one-shot transition (HPnGs) have been introduced together with an algorithm to analyze their underlying state space using a conditioning/deconditioning approach. In this paper we propose a considerably more efficient algorithm for analysing HPnGs. The proposed algorithm maps the underlying state-space onto a plane for all possible firing times of the general transition s and for all possible systems times t. The key idea of the proposed method is that instead of dealing with infinitely many points in the t-s-plane, we can partition the state space into several regions, such that all points inside one region are associated with the same system state. To compute the probability to be in a specific system state at time τ, it suffices to find all regions intersecting the line t = τ and decondition the firing time over the intersections. This partitioning results in a considerable speed-up and provides more accurate results. A scalable case study illustrates the efficiency gain with respect to the previous algorithm.
KeywordsSystem State General Transition Occurrence Time Deterministic Region Time Automaton
Unable to display preview. Download preview PDF.
- 6.David, R., Alla, H.: Discrete, Continuous, and Hybrid Petri Nets, 2nd edn. Springer (2010)Google Scholar
- 7.Ghasemieh, H., Remke, A., Haverkort, B., Gribaudo, M.: Region-based analysis of hybrid Petri nets with a single general one-shot transition: extended version. Technical report, University of Twente (2012), http://wwwhome.cs.utwente.nl/~anne/techreport/std.pdf
- 8.Gribaudo, M., Remke, A.: Hybrid Petri Nets with General One-Shot Transitions for Dependability Evaluation of Fluid Critical Infrastructures. In: 2010 IEEE 12th International Symposium on High Assurance Systems Engineering, pp. 84–93. IEEE CS Press (November 2010)Google Scholar
- 9.Gribaudo, M., Remke, A.: Hybrid petri nets with general one-shot transitions: model evolution. Technical report, University of Twente (2010), http://wwwhome.cs.utwente.nl/~anne/techreport/hpng.pdf
- 10.Kartson, D., Balbo, G., Donatelli, S., Franceschinis, G., Conte, G.: Modelling with Generalized Stochastic Petri Nets, 1st edn. John Wiley & Sons, Inc. (1994)Google Scholar