A Framework for Supporting Intelligent Fault and Performance Management for Communication Networks

Hongjun Li and John S. Baras

Center for Satellite and Hybrid Communication Networks
Department of Electrical and Computer Engineering
University of Maryland,
College Park, MD 20742
{hjli,baras}@isr.umd.edu

Abstract. In this paper, we present a framework for supporting intelligent fault and performance management for communication networks. Belief networks are taken as the basis for knowledge representation and inference under evidence. When using belief networks for diagnosis, we identify two questions: When can I say that I get the right diagnosis and stop? If right diagnosis has not been obtained yet, which test should I choose next? For the first question, we define the notion of right diagnosis via the introduction of intervention networks. For the second question, we formulate the decision making procedure using the framework of partially observable Markov decision processes. A heuristic dynamic strategy is proposed to solve this problem and the effectiveness is shown via simulation.

LNCS 2216, p. 227 ff.

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Online publication: October 10, 2001
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