FAULT DETECTION AND PREDICTION FOR MANAGEMENT OF COMPUTER NETWORKS

摘要

An improved system and method for network fault and anomaly detection is provided based on the statistical behavior of the management information base (MIB) variables. The statistical and temporal information at the variable level is obtained from the sensors associated with the MIB variables. Each sensor performs sequential hypothesis testing based on the Generalized Likelihood Ratio (GLR) test. The ouputs of the individual sensors are combined using a fusion center, which incorporates the interdependencies of the MIB variables. The fusion center provides temporally correlated alarms that are indicative of network problems. The detection scheme relies on traffic measurement and is independent of specific fault descriptions.