An improved network performance anomaly detection and localization algorithm

In this paper, we introduce a network performance anomaly detection and localization method based on active probing, aiming at avoiding waste of unnecessary probes and reducing detecting time by decreasing selecting rounds in detection phase. We propose a method of classifying detection strategies in order to find a balance between extra calculation and link load. Also we optimized the procedures of one of the strategies so that instead of finding a local optimal solution, we get a global optimal approach. An algorithm that can adapt to multi anomaly link networks is proposed and several issues during detection phase were being discussed. Finally we simulate a former representative algorithm and our improved method on different network topologies. The results show that our improved algorithm outperforms the former one in both probe selecting rounds during detection phase by 10%.