A Parametric Colored Petri Net Model of a Switched Network

Zaitsev, Dmitry A.; Shmeleva, Tatiana R.

doi:10.4236/ijcns.2011.41008

Cited by 13 publications

(6 citation statements)

References 5 publications

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“…According to this approach, the decision variables can be called parameters of the Petri net model and they might be the initial marking of certain places, weight of some arcs between nodes of the net, delay times associated to a given set of transitions, etc. [9].…”

Section: Petri Nets In Decision Support Systemsmentioning

confidence: 99%

Petri Net Models Optimized for Simulation

Latorre-Biel¹,

Jiménez‐Macías²

2019

Simulation Modelling Practice and Theory

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Petri nets and simulation are a modeling paradigm and a tool, respectively, which may be successfully combined for diverse applications, such as performance evaluation, decision support, or training on complex systems. Simulation may require significant computer resources; hence, in this chapter, two Petri net-based formalisms are analyzed for profiting from their respective advantages for modeling, simulation, and decision-making support: a set of alternative Petri nets and a compound Petri net. These formalisms, as well as the transformation algorithms between them, are detailed and an illustrative example is provided. Among the main advantages of these formalisms, their intuitive application for modeling discrete event systems in the process of being designed, as well as the compactness that may present the resulting model, in the case of a compound Petri net, leading to efficient decision making, can be mentioned.

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Section: Petri Nets In Decision Support Systemsmentioning

confidence: 99%

Petri Net Models Optimized for Simulation

Latorre-Biel¹,

Jiménez‐Macías²

2019

Simulation Modelling Practice and Theory

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“…Giving diverse feasible values to these parameters, it is possible to specify different alternative structural configurations of the DES. These Petri nets can be called parametric, parameterized, parameterized, or compound Petri nets [6].…”

Section: Complexitymentioning

confidence: 99%

“…In fact, they mainly focus on the decision-making process to select one alternative structural configuration of the DES [6,8,21,22].…”

Section: Complexitymentioning

confidence: 99%

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Equivalent and Efficient Optimization Models for an Industrial Discrete Event System with Alternative Structural Configurations

2018

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Discrete event systems in applications, such as industry and supply chain, may show a very complex behavior. For this reason, their design and operation may be carried out by the application of optimization techniques for decision making in order to obtain their highest performance. In a general approach, it is possible to implement these optimization techniques by means of the simulation of a Petri net model, which may require an intensive use of computational resources. One key factor in the computational cost of simulation-based optimization is the size of the model of the system; hence, it may be useful to apply techniques to reduce it. This paper analyzes the relationship between two Petri net formalisms, currently used in the design of discrete event systems, where it is usual to count on a set of alternative structural configurations. These formalisms are a particular type of parametric Petri nets, called compound Petri nets, and a set of alternative Petri nets. The development of equivalent models under these formalisms and the formal proof of this equivalence are the main topics of the paper. The basis for this formal approach is the graph of reachable markings, a powerful tool able to represent the behavior of a discrete event system and, hence, to show the equivalence between two different Petri net models. One immediate application of this equivalence is the substitution of a large model of a system by a more compact one, whose simulation may be less demanding in the use of computational resources.

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“…In this paper, we use, among others, stochastic Petri nets as a predictive model. Regarding the stochastic Petri nets, such as queueing Petri nets, and their usage in a networking context, so far they have mainly been used to model specific network components at a high level of detail but with limited scope as, for example in [37,21]. However, an end-to-end modeling approach is crucial in modern virtualized systems.…”

Section: Performance Models For Data Center Networkmentioning

confidence: 99%

Flexible Performance Prediction of Data Center Networks using Automatically Generated Simulation Models

Rygielski

Kounev

Tran-Gia

2015

Proceedings of the Eighth EAI International Conference on Simulation Tools and Techniques

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Using different modeling and simulation approaches for predicting network performance requires extensive experience and involves a number of time consuming manual steps regarding each of the modeling formalisms. In this paper, we propose a generic approach to modeling the performance of data center networks. The approach offers multiple performance models but requires to use only a single modeling language. We propose a two-step modeling methodology, in which a high-level descriptive model of the network is built in the first step, and in the second step model-to-model transformations are used to automatically transform the descriptive model to different network simulation models. We automatically generate three performance models defined at different levels of abstraction to analyze network throughput. By offering multiple simulation models in parallel, we provide flexibility in trading-off between the modeling accuracy and the simulation overhead. We analyze the simulation models by comparing the prediction accuracy with respect to the simulation duration. We observe, that in the investigated scenarios the solution duration of coarser simulation models is up to 300 times shorter, whereas the average prediction accuracy decreases only by 4 percent.

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A Parametric Colored Petri Net Model of a Switched Network

Cited by 13 publications

References 5 publications

Petri Net Models Optimized for Simulation

Petri Net Models Optimized for Simulation

Equivalent and Efficient Optimization Models for an Industrial Discrete Event System with Alternative Structural Configurations

Flexible Performance Prediction of Data Center Networks using Automatically Generated Simulation Models

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