An Event-Driven Fault Localization Algorithm Based on Incremental Bayesian Suspected Degree
Zhang Cheng; Liao Jian-xin; Zhu Xiao-min
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China; EB Information Technology Co. Ltd., Beijing 100083, China
Abstract：Most fault localization techniques is based on time windows. The size of time windows impacts on the accuracy of the algorithms greatly. This paper takes weighted bipartite graph as fault propagation model and proposes a heuristic fault localization algorithm based on Incremental Bayesian Suspected Degree (IBSD) to eliminate the above shortcomings. IBSD sequentially analyzes the incoming symptoms in an event-driven way and incrementally computes the Bayesian Suspected Degree and determine the most probable fault set for the current observed symptoms. Simulation results show that the algorithm has high fault detection ratio as well as low false positive ratio and has a good performance even in the presence of unobserved alarms. The algorithm which has a polynomial computational complexity could be applied to large scale communication network.
2009, Vol. 31 
