A formal framework for the decentralised diagnosis of large scale discrete event systems and its application to telecommunication networks
Date
2005
Authors
Pencole, Yannick
Cordier, Marie-Odile
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Publisher
Elsevier
Abstract
We address the problem of diagnosing large discrete event systems. Given a flow of observations from the system, the goal is to explain these observations on-line by identifying and localising possible failures and their consequences across the system. Model-based diagnosis approaches deal with this problem but, apart very recent proposals, either they require the computation of a global model of the system which is not possible with large discrete event systems, or they cannot perform on-line diagnosis. The contribution of this paper is the description and the implementation of a formal framework for the on-line decentralised diagnosis of such systems, framework which is based on the "divide and conquer" principle and does not require the global model computation. This paper finally describes the use of this framework in the monitoring of a real telecommunication network.
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Keywords: Algorithms; Artificial intelligence; Computational complexity; Discrete time control systems; Large scale systems; Problem solving; Decentralized models; Discrete event systems; Distributed artificial intelligence; Fault propagation; Telecommunication net Decentralised model; Discrete event systems; Distributed artificial intelligence; Fault propagation; Model-based diagnosis; Telecommunication networks
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Source
Artificial Intelligence
Type
Journal article
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2037-12-31
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