Weak invariant simulation: Properties and algorithms | IEEE Conference Publication | IEEE Xplore

Weak invariant simulation: Properties and algorithms

Publisher: IEEE

Abstract:

Large-scale networks consisting of similar similar subprocesses can conveniently be modeled as Parameterized Discrete Event Systems (PDES). This modeling is particularly ...View more

Abstract:

Large-scale networks consisting of similar similar subprocesses can conveniently be modeled as Parameterized Discrete Event Systems (PDES). This modeling is particularly useful when the number of subprocesses is arbitrary, unknown or time-varying. Unfortunately, key problems such as checking the nonblocking property in these networks are undecidable. Moreover, mathematical tools supporting analysis of these networks are very limited. In previous work, we introduced weak invariant simulation in its preliminary form as a new mathematical notion for analysis of deterministic PDES and for defining tractable subclasses of PDES. In this paper, we broaden the definition of weak invariant simulation for nondeterministic PDES and give more insight into its properties. We compare weak invariant simulation to other simulation relations in the literature. Moreover, we propose a method to check whether a process weakly invariantly simulates another process with respect to a specific subalphabet. The greatest lower bound of all weak invariant simulations between two processes is also introduced. To illustrate the significance of weak invariant simulation, we outline its application to deadlock analysis of parameterized networks.
Date of Conference: 17-19 June 2013
Date Added to IEEE Xplore: 15 August 2013
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Publisher: IEEE
Conference Location: Washington, DC, USA

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