Using Network Fault Predictions to Enable IP Traffic Management

IP traffic management is important for the continued growth of the Internet. Several traffic management algorithms exist today. However, to enable these algorithms it is necessary to provide reliable alarms relating to network performance bottlenecks and failures. In this work we propose an algorithm to obtain reliable predictive alarms for network fault conditions. The algorithm is based on modeling network fault behavior. The algorithm has been successfully tested on two production networks. Predictive alarms were obtained for four different types of failures: file server failures, network access problems, protocol implementation errors, and runaway processes. The potential of using this model to do fault classification is also discussed. In addition, it is shown that the proposed algorithm performs better than the majority-vote scheme.

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