The Conversion of Dynamic Fault Trees to Stochastic Petri Nets, as a case of Graph Transformation

AbstractA model-to-model transformation from Dynamic Fault Trees to Stochastic Petri Nets, by means of graph transformation rules, is presented in this paper. Dynamic Fault Trees (DFT) are used for the reliability analysis of complex and large systems and represent by means of gates, how combinations or sequences of component failure events, lead to the failure of the system. DFTs need the state space solution which can be obtained by converting a DFT to a Stochastic Petri Net: this task is expressed by means of graph transformation rules, and is applied to a case of system

Second Workshop on Modelling of Objects, Components and Agents

This report contains the proceedings of the workshop Modelling of Objects, Components, and Agents (MOCA'02), August 26-27, 2002.The workshop is organized by the 'Coloured Petri Net' Group at the University of Aarhus, Denmark and the 'Theoretical Foundations of Computer Science' Group at the University of Hamburg, Germany. The homepage of the workshop is: http://www.daimi.au.dk/CPnets/workshop02

Timed Petri net models of queueing systems

It is shown that for timed Petri nets with exponentially distributed firing times (M-timed Petri nets), the state space can be generated directly from net specifications, and then the stationary probabilities of states can be obtained by standard methods, developed for analysis of (continuous-time) Markov chains. Numerous performance measures can be derived from stationary probabilities of states. For unbounded nets (models of open network systems are usually unbounded), the state space is infinite. A transformation is thus needed that folds this infinite space into a finite representation, used for effective evaluation of probabilities. The author presents a short theoretical background for performance evaluation using timed Petri nets, followed by several examples of closed and open network models of simple computer systems

Compositional Performance Modelling with the TIPPtool

Stochastic process algebras have been proposed as compositional specification formalisms for performance models. In this paper, we describe a tool which aims at realising all beneficial aspects of compositional performance modelling, the TIPPtool. It incorporates methods for compositional specification as well as solution, based on state-of-the-art techniques, and wrapped in a user-friendly graphical front end. Apart from highlighting the general benefits of the tool, we also discuss some lessons learned during development and application of the TIPPtool. A non-trivial model of a real life communication system serves as a case study to illustrate benefits and limitations