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Colored Petri Nets: A Graphical Language For Formal Modeling and Validation of Concurrent Systems


Colored Petri Nets, illustration

Credit: xtremetips.com

The vast majority of IT systems today can be characterized as concurrent and distributed in that their operation inherently relies on communication, synchronization, and resource sharing between concurrently executing software components and applications. This development was accelerated first through the pervasive presence of the Internet as a communication infrastructure and more recently by cloud- and Web-based services, mobile applications, and multicore computing architectures.

Colored Petri Nets, or CPNs, combine Petri nets with a programming language to obtain a scalable modeling language for concurrent systems. Petri nets provide the formal foundation for modeling concurrency and synchronization; a programming language provides the primitives for modeling data manipulation and creating compact and parameterizable models. In this article, we offer an example-driven introduction to the core syntactical and semantical constructs of the CPN modeling language and survey how quantitative and qualitative behavioral properties of CPN models can be validated through simulation-based performance analysis and explicit state-space exploration. We also give an overview of CPN Tools that provide software-tool support for the practical use of CPNs and pointers to projects where CPN technology has been put to practical use in an industrial setting. As we proceed, we give a historical perspective on the research contributions that led to development of CPN technology.


Comments


Dmitry Zaitsev

In CPN Tools, we built models for manifold networking technologies: Provider Backbone Bridge, Ethernet, IP, MPLS, Bluetooth, E6, Dynamic Routing etc which are delivered via the tools website http://cpntools.org/documentation/examples/start We use CPN Tools as GPSS for performance evaluation. Undoubtable benefits consist in vivid graphical language enriched with the functional programming language ML. For modeling new networking technologies we find CPN Tools even more flexible than ns. For processing of statistical information on-fly we supplement models with special measuring subnets.

Dmitry Zaitsev
http://member.acm.org/~daze


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