Petri nets and other models of concurrency

Nielsen, Mogens; Sassone, Vladimiro

doi:10.1007/3-540-65306-6_23

Cited by 4 publications

(3 citation statements)

References 89 publications

(122 reference statements)

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“…The FSPN modeling methodology is consistent with that of other Petri nets formalisms [14], [15] with its unique rules. We give a 6-step procedure to construct sensor network models with FSPNs.…”

Section: Formalizationmentioning

confidence: 63%

Hybrid Modeling Method Based on FSPN for Sensor Networks

Wan¹,

Zhou

Deng

et al. 2013

AMM

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Sensor networks play a central role in the Internet of things, which attracts lots of attentions recently. Mathematical models are of much help to explore intricate scheduling on the sensor node or interactions between different sensor nodes. Although many existing approaches have shown that the sensor network behaves like a hybrid system, where discrete character and continuous character exist together, few of them have attempted to consider two characters together. In this paper, we propose a novel quantitative modeling framework based on Fluid Stochastic Petri nets (FSPNs), and provide comprehensive theoretical analysis to a typical sensor network example. Our modeling framework, which combines advantages of both Stochastic Petri Nets (SPNs) and Hybrid Functional Petri Nets (HFPNs), reflects the hybrid nature of sensor networks, and at the same time eases the problem of state space explosion. The modeling mechanism proposed in this paper constructs sensor network models that are comprised of both stochastic processes and fluid flow approximation technique. From the evaluation, it's shown that the new method performs well.

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Section: Formalizationmentioning

confidence: 63%

Hybrid Modeling Method Based on FSPN for Sensor Networks

Wan¹,

Zhou

Deng

et al. 2013

AMM

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“…Information on the Semantic Web is described with ontology description languages, such as OWL, RDF and OWL-S. Since Petri nets have a powerful capability to model events and states in information processing systems and to formally analyze the processes (Nielsen & Sassone, 1988), the aim of mapping ontology description languages into Petri nets is to use the formal analysis of Petri nets to supplement the functions of ontologies. Nowadays, OWL-S and DAML-S (DAML-Service) are used to specify the process of Web service application.…”

Section: Mapping Ontology Description Languages Into Petri Netsmentioning

confidence: 99%

A literature overview of knowledge sharing between Petri nets and ontologies

Cheng

2016

The Knowledge Engineering Review

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Knowledge representation is a subarea of artificial intelligence concerned with using formal symbols to represent a set of facts within a knowledge domain. Two popular knowledge representation languages, namely Petri net and ontology, are promising knowledge sharing and reusing methods in knowledge engineering. The combination of Petri net and ontology can facilitate achieving complementary advantages. Currently, many efforts have been done on knowledge sharing between Petri nets and ontologies. To investigate these issues and more importantly serve as identifying the direction of knowledge sharing between Petri nets and ontologies, in this paper we give a comprehensive literature overview of knowledge sharing between Petri net models and ontology models to satisfy the obvious need. In detail, we discuss the knowledge sharing from two aspects: the different knowledge representation approaches of ontology to represent and reason Petri net and issues of constructing Petri net from ontology. In addition, other important issues on applications and directions for future research are discussed in detail.

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“…Our interest, instead, resides on abstract models that capture the mathematical essence of such spaces, possibly axiomatically, roughly in the same way as a prime algebraic domain (or, equivalently, a prime event structure [96,98]) models the computations of a net (see, e.g., [70]). The research detailed in [58, 24, 59, 86, 87] identifies such structures as symmetric monoidal categories -where objects are states, i.e., multisets of tokens, arrows are processes, and the tensor product and the arrow composition model, respectively, the operations of parallel and sequential composition of processes.…”

Section: Petri Nets In the Smallmentioning

confidence: 99%