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Optimization of fault diagnosis based on the combination of Bayesian Networks and Case-Based Reasoning

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5 Author(s)
Leila Bennacer ; Alcatel-Lucent Bell Labs France, Centre de Villarceaux, Route de Villejust, 91620 Nozay, France ; Laurent Ciavaglia ; Abdelghani Chibani ; Yacine Amirat
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Fault diagnosis is one of the most important tasks in fault management. The main objective of the fault management system is to detect and localize failures as soon as they occur to minimize their effects on the network performance and therefore on the service quality perceived by users. In this paper, we present a new hybrid approach that combines Bayesian Networks and Case-Based Reasoning to overcome the usual limits of fault diagnosis techniques and reduce human intervention in this process. The proposed mechanism allows identifying the root cause failure with a finer precision and high reliability while reducing the process computation time and taking into account the network dynamicity.

Published in:

2012 IEEE Network Operations and Management Symposium

Date of Conference:

16-20 April 2012