Stochastic Petri nets: Properties, applications and tools

Florin, Gérard; Fraize, C.; Natkin, Stéphane

doi:10.1016/0026-2714(91)90009-v

Cited by 54 publications

(19 citation statements)

References 9 publications

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“…The colored Petri net (CPN) is able to represent complex information in the token, and the timed PN includes time to represent firing delay, and so on (Florin et al 1991;Zuberek 1991). These various extended PNs have been applied to context modeling for various purposes.…”

Section: Petri Net (Pn)mentioning

confidence: 99%

Petri net-based context modeling for context-aware systems

Han

Youn

2011

Artif Intell Rev

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The context-aware services require to efficiently perceive not only the user requirements but also the context of the environment to provide customized services to the user. To efficiently develop the context-aware applications a systematic methodology correctly specifying the relation among dynamically changing contexts is essential. Here the context model simplifying the manipulation of complex contexts is a key accessor for the specification and analysis of the service. Among various modeling approaches such as timed automata (Tang and You in Intell Automat Soft Comput 16 (4):605-619, 2010), workflow (Rosemann et al. in Understanding context-awareness in business process design, 2010), Petri net (PN) (Jørgensen et al. in Innovat Syst Softw Eng 5(1):13-25, 2009), etc.developed for context-aware system, the PN-based approach has been recognized as one of the most effective one. In this paper we identify the issues of how the contexts are modeled and what kinds of the requirements needs to be considered in the context processing. We then discuss various Petri net (PN)-based modeling methodologies concerning the five important features for context processing: relationships and dependencies, time constraint, resource constraint, usability of modeling formalisms, and context identification. The study reveals that the approach effectively allowing both the time and resource constraints in the model while supporting other important properties needs to be developed further for accurately assess the context-aware systems. Also, the expandability and scalability issue need to be investigated.

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Section: Petri Net (Pn)mentioning

confidence: 99%

Petri net-based context modeling for context-aware systems

Han

Youn

2011

Artif Intell Rev

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“…A transition is enable if each of its input places contains at least one token. Stochastic Petri net or SPN [16] is a 6-tuple (P, T, I, O, M 0 , ) where P, T, I, O and M 0 has the same meaning of a Petri net and  is set of average firing rate of transitions.…”

Section: Stochastic Petri Netsmentioning

confidence: 99%

Formal approach on modeling and predicting of software system security: Stochastic petri net

Motameni

2015

JAIDM

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To evaluate and predict component-based software security, a two-dimensional model of software security is proposed by Stochastic Petri Net in this paper. In this approach, the software security is modeled by graphical presentation ability of Petri nets, and the quantitative prediction is provided by the evaluation capability of Stochastic Petri Net and the computing power of Markov chain. Each vulnerable component is modeled by Stochastic Petri net and two parameters, Successfully Attack Probability (SAP) and Vulnerability Volume of each component to another component. The second parameter, as a second dimension of security evaluation, is a metric that is added to modeling to improve the accuracy of the result of system security prediction. An isomorphic Markov chain is obtained from a corresponding SPN model. The security prediction is calculated based on the probability distribution of the MC in the steady state. To identify and trace back to the critical points of system security, a sensitive analysis method is applied by derivation of the security prediction equation. It provides the possibility to investigate and compare different solutions with the target system in the designing phase.

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“…As per reference [8] and [9], in a Stochastic Petri Net (SPN), the firing time is an exponentially distributed random variab le. Thus the marking sequence in a SPN obtained fro m the firings, is isomorphic to a continuous time Markov Chain.…”

Section: Petri Netsmentioning

confidence: 99%

Generalized Stochastic Petri Nets for Reliability Analysis of Lube Oil System with Common-Cause Failures

Thangamani¹

2012

AJCAM

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A very high level of availab ility is crucial to the economic operation of modern power plants, in view of the huge expenditure associated with their failures. Th is paper deals with the availab ility analysis of a Lube oil system used in a combined cycle power plant. The system is modeled as a Generalized Stochastic Petri Net (GSPN) taking into consideration of partial failures of their subsystems and common-cause failures; analyzed using Monte Carlo Simu lation approach. The major benefit of GSPN approach is hardware, software and human behavior can be modeled using the same language and hence more suitable to model co mplex system like power p lants. The superiority of this approach over others such as network, fault tree and Markov analysis are outlined. The numerical estimates of availability, failure criticality index o f various subsystems, co mponents causing unavailability of lube oil system are brought out. The proposed GSPN is a pro mising tool that can be conveniently used to model and analyze any co mple x systems.

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Stochastic Petri nets: Properties, applications and tools

Cited by 54 publications

References 9 publications

Petri net-based context modeling for context-aware systems

Petri net-based context modeling for context-aware systems

Formal approach on modeling and predicting of software system security: Stochastic petri net

Generalized Stochastic Petri Nets for Reliability Analysis of Lube Oil System with Common-Cause Failures

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