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Adaptive Petri Nets – A Petri Net Extension for Reconfigurable Structures

Authors:
Carl Mai
René Schöne
Johannes Mey
Thomas Kühn
Uwe Aßmann

Keywords: Petri nets; Reconfigurable Petri nets; Inhibitor Arcs; Analysis

Abstract:
Petri nets are used to formally model the behavior of systems. However, when these systems dynamically change, e.g., due to context dependence, modeling gets complex and cumbersome since Petri nets are low-level and can not express dynamic changing parts. Expressing dynamically changing parts of the system directly within Petri nets increases the clarity and allows for modeling complex, context dependent, systems. While various approaches can be found in the literature, their integration into the Petri net ecosystem is often not considered. This restricts the available tools and analysis techniques to those, which can handle that custom net type. We present adaptive Petri nets, an extension to Petri nets, which directly expresses variability within the net. Our approach integrates well with other Petri net extensions, such as colored tokens, inhibitor arcs or hierarchy. Most importantly, it is possible to convert an adaptive Petri net to a semantically equivalent Petri net with inhibitor arcs. This work presents the formalism of adaptive Petri nets, how they can be flattened to Petri nets with inhibitor arcs and their graphical representation. The feasability and usability is demonstrated on two examples that are modeled, flattened and analyzed.

Pages: 15 to 23

Copyright: Copyright (c) IARIA, 2018

Publication date: February 18, 2018

Published in: conference

ISSN: 2308-4146

ISBN: 978-1-61208-610-1

Location: Barcelona, Spain

Dates: from February 18, 2018 to February 22, 2018