Facing Fault Management as It Is, Aiming for What You Would Like It to Be

Telecommunication systems are built with extensive redundancy and complexity to ensure robustness and quality of service. Such systems requires complex fault identification and management tools. Fault identification and management are generally handled by reducing the number of alarm events (symptoms) presented to the operating engineer through monitoring, filtering and masking. The goal is to determine and present the actual underlying fault. Fault management is a complex task, subject to uncertainty in the symptoms presented. In this paper two key fault management approaches are considered: (i) rule discovery to attempt to present fewer symptoms with greater diagnostic assistance for the more traditional rule based system approach and (ii) the induction of Bayesian Belief Networks (BBNs) for a complete `intelligent' approach. The paper concludes that the research and development of the two target fault management systems can be complementary.

• Type: Journal
• Year: 2002
• Where: SOFTWARE
• Authors: Roy Sterritt
• Keywords: Applied Computing, Complex Fault Identification, Fault Identification, Fault Management, SOFTWARE 2002