Reliability analysis is often based on stochastic discrete event models like Markov models or stochastic Petri nets. For complex dynamical systems with numerous components, analytical expressions of the steady state are tedious to work out because of the combinatory explosion with discrete models. Moreover, the convergence of stochastic estimators is slow. For these reasons, fluidification can ...

SUMMARY To investigate biomolecular networks, Snoopy provides a unifying Petri net framework comprising a family of related Petri net classes. Models can be hierarchically structured, allowing for the mastering of larger networks. To move easily between the qualitative, stochastic and continuous modelling paradigms, models can be converted into each other. We get models sharing structure, but s...

In concurrent real-time processes, the speed of individual components has a double impact: on the one hand, the overall latency of a compound process is affected by the latency of its components. But, if the composition has race conditions, the very outcome of the process will also depend on the latency of component processes. Using stochastic Petri nets, we investigate the probability of a tra...

In this paper we deene a Stochastic Petri Net (SPN) semantics for Stochastic Process Algebras (SPAs), a recently introduced formalism that ooers a novel approach for performance modeling. The proposed semantics is evaluated in terms of three criteria: Con-currency and Retrievability, as deened by Olderog for untimed net semantics, and Markov Equivalence for the stochastic aspects.

Introduction Stochastic Petri net based Markov modeling is a potentially very powerful and generic approach for evaluating the performance and depend ability of many di erent systems such as computer systems communication networks manufacturing sys tems etc As a consequence of their general appli cability SPN based Markov models form the basic solution approach for several software packages tha...

Petri nets represent a modeling paradigm which allows to build general models by using a small number of graphical primitives. The strong point of Petri nets lies in their ability to model system aspects such as concurrency and synchronization and to represent these aspects graphically. Due to this reason, stochastic Petri nets (SPNs) are frequently used for model-based performance and dependab...

The Stochastic Petri Net Package (SPNP) [2] is a versatile modeling tool for solution of Stochastic Petri Net (SPN) models. The SPN models are described in the input language for SPNP called CSPL (C-based SPN Language) which is an extension of the C programming language [8] with additional constructs which facilitate easy description of SPN models. Moreover, if the user does not want to describ...