The complexity of gene regulatory network models stems from the fact that the models should be able to represent continuous, discrete as well as stochastic aspects of gene regulation. Hybrid stochastic Petri nets are the models, which can fairly incorporate all these aspects while keeping the model as simple as possible for biologists. This paper constructs an Hybrid Petri net model of the fiss...

Ordinary t-timed modular Petri Nets are used for modeling, analysis, synthesis and performance evaluation of random topology dedicated production systems. Each system is first decomposed into production line, assembly, disassembly and parallel machine modules followed by derivation of their modular Petri Net models. Two sets of modules, generic and generalized respectively, are derived correspo...

There are widely used analysis techniques for stochastic Petri nets with phase type (PH) distributed firing times. These techniques are based on the generation of an expanded Markov chain that describes the behaviour of the marking process and additionally the phase processes of the involved PH distributions. In this paper we investigate the use of a similar approach when the firing time distri...

In this paper we evaluate the performance of design alternatives for Web proxy cache architectures. Our performance study employs deterministic and stochastic Petri nets (DSPN) as stochastic modeling formalism because DSPN provide an illustrative graphical representation. The presented DSPN models address in particular the sensitivity of the performance of proxy cache architectures on the traff...

Queueing Petri nets are a powerful formalism that can be exploited for modeling distributed systems and analyzing their performance and scalability. By combining the modeling power and expressiveness of queueing networks and stochastic Petri nets, queueing Petri nets provide a number of advantages. In this paper, we present our tool QPME (Queueing Petri net Modeling Environment) for modeling an...

Based on the Extended Colored Stochastic Petri Nets (ECSPN), the workflow system was modeled and simulated. To improve described capacity of the traditional Petri nets, a model of the extended colored stochastic Petri nets is proposed, and then an instance is given to explain how to model workflow system with priority queuing and multi-instances. Through analysis of the simulation data of the m...

In this report we present an extension to Continuous Time Bayesian Networks (CTBN) called Generalized Continuous Time Bayesian Networks (GCTBN). The formalism allows one to model, in addition to continuous time delayed variables (with exponentially distributed transition rates), also non delayed or “immediate” variables, which act as standard chance nodes in a Bayesian Network. This allows the ...

Stochastic Petri nets (SPNs) with generally distributed firing times can model a large class of systems, but simulation is the only feasible approach for their solution. We explore a hierarchy of SPN classes where modeling power is reduced in exchange for an increasingly efficient solution. Generalized stochastic Petri nets (GSPNs), deterministic and stochastic Petri nets (DSPNs), semi-Markovia...

Stochastic simulations are able to capture the fine grain behaviour and randomness of outcome of biological networks not captured by deterministic techniques. As such they are becoming an increasingly important tool in the biological community. However, current efforts in the stochastic simulation of biological networks are hampered by two main problems: firstly the lack of complete knowledge o...

Queueing Petri nets are a powerful formalism that can be exploited for modeling distributed systems and analyzing their performance and scalability. By combining the modeling power and expressiveness of queueing networks and stochastic Petri nets, queueing Petri nets provide a number of advantages. In this paper, we present Version 2.0 of our tool QPME (Queueing Petri net Modeling Environment) ...