Probabilistic fault diagnosis in communication systems through incremental hypothesis updating

  • Authors:
  • M. Steinder;A. S. Sethi

  • Affiliations:
  • IBM T.J. Watson Research Center, 19 Skyline Dr. Hawthorne, NY;Computer and Information Sciences, University of Delaware, 102 Smith Hall, Newark, DE

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2004

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Abstract

This paper presents a probabilistic event-driven fault localization technique, which uses a probabilistic symptom-fault map as a fault propagation model. The technique isolates the most probable set of faults through incremental updating of a symptom-explanation hypothesis. At any time, it provides a set of alternative hypotheses, each of which is a complete explanation of the set of symptoms observed thus far. The hypotheses are ranked according to a measure of their goodness. The technique allows multiple simultaneous independent faults to be identified and incorporates both negative and positive symptoms in the analysis. As shown in a simulation study, the technique offers close-to-optimal accuracy and is resilient both to noise in the symptom data and to inaccuracies of the probabilistic fault propagation model.