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G-networks with Propagating Resets via RCAT

Peter G. Harrison

Conference or Workshop Paper
MAMA 2003, Special issue on the 5th workshop on Mathematical Performance Modeling and Analysis
August, 2003
ACM SIGMETRICS Performance Evaluation Review
Volume 31
Issue 2
ACM Press
DOI 10.1145/959143.959144

Stationary Markovian networks, defined by a collection of cooperating agents, can be solved for their equilibrium state probability distribution by a new compositional method that computes their reversed Markov process, under appropriate conditions. We apply this approach to G-networks with chains of triggers and generalised resets, which have some quite distinct properties from the resets proposed recently.

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