نتایج جستجو برای: generalized stochastic petri net
تعداد نتایج: 385373 فیلتر نتایج به سال:
Biological systems are often very complex so that an appropriate formalism is needed for modeling their behavior. Hybrid Petri nets, consisting of timediscrete as well as continuous Petri net elements, have proven to be ideal. This formalism was implemented based on the Modelica language. Several Petri net components are structured within an advanced Petri net library. A special sub-library con...
Priority speciications ooer a convenient description technique to resolve connicts in favour of particular actions. Besides specifying the functional behaviour of a system, priorities have also become important in the eld of performance analysis using stochastic Petri nets, where priorities are implicitly given by separating transitions into immediate and timed. For performance analysis of such...
In this paper, we show how to design a perfect simulation for Markovian fork-join networks, or equivalently, free-choice Petri nets. For pure fork-join networks and for event graphs, the simulation time can be greatly reduced by using extremal initial states, namely blocking states, although such nets do not exhibit any natural monotonicity property. Another approach for perfect simulation of p...
Analytical modeling is a crucial part in the analysis and design of computer systems. Stochastic Petri Nets represent a powerful tool, widely used for dependability, performance and performability modeling. Many structural and stochastic extensions have been proposed so as to increase their modeling power. In this paper we review the main structural and stochastic extensions of Petri nets, by p...
Coloured Petri nets are imperative for studying bigger biological models, particularly, those which expose repetition of components. Such models can be easily scaled by minor changes of a few parameters. Similarly, studying certain biological phenomena necessitates the existence of discrete and continuous variables as well as continuous and stochastic processes in one and the same model. Thus, ...
Topics: higher-level net models, timed and stochastic nets. Abstract System analysis is often done due to qualitative and quantitative aspects. Queueing networks and Petri nets are suitable and wide spread model worlds for such a form of analysis, because for both a well founded theory exists. The problem is that Petri nets and queueing networks are only suitable for qualitative analysis resp. ...
The stochastic modeling of biological systems is gaining more and more attention when stochastic fluctuations need to be described. On the other hand, the biological systems under investigation become much more complex than before. Traditional modeling methods like stochastic Petri nets do not easily scale and thus become difficult to tackle this situation. This paper aims to present a colored ...
This paper is concerned with defining causality semantics for infinite executions of Petri nets with inhibitor arcs. We first show how one can deal with infinite step sequences and the corresponding occurrence nets (processes) and causal structures. We then discuss how to improve the succinctness of both finite and infinite processes generated from step sequences. In the latter case, the propos...
In this paper, the performance evaluation of CEBus protocol using Stochastic Timed Petri Nets is proposed. The aim of this paper is to present the model and the performance evaluation of CEBus protocol based on three priority by Stochastic Timed Petri Nets. For this, modular and composite Petri Nets models of CEBus protocol are proposed. For the performance evaluation, Stochastic Timed Petri Ne...
The paper presents the current status of the software tool TimeNET. It supports modeling and performance evaluation of stochastic models, including extended deterministic and stochastic Petri nets, colored stochastic Petri nets, and Markov chains as well as UML extensions. Among its main characteristics are simulation and analysis modules for stationary and transient evaluation of Petri nets in...
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