Network faults classification using FCM

Mo Adda, Karwan Qader

Research output: Contribution to conferencePaperpeer-review


The last decade has witnessed an increasing usage of data mining techniques such as clustering into many applications including network faults classification. In communication networks often large volume of network faults are generated. Even a single fault may result in large number of alarms causing information redundancy. Providing a coherent classification scheme would certainly help network management process, avoid system breakdown, by isolating faults earlier, and predict peculiar events. In this paper, we survey different clustering algorithms to classify network faults and provide an evaluation based on the speed, accuracy, efficiency and cost. From accuracy point of view some of the algorithms yield high accuracy as indicated in the literature. Out of them Fuzzy Cluster-Means is considered more suitable for network faults classification based on the context in which they are applied.
Original languageEnglish
Publication statusPublished - Oct 2013
Event17th International Conference on Distributed Computer and Communication Networks - Moscow, Russian Federation
Duration: 7 Oct 201310 Oct 2013


Conference17th International Conference on Distributed Computer and Communication Networks
Country/TerritoryRussian Federation


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