Online network performance degradation localization using probabilistic inference and change detection

Detecting and localizing performance degradations is a difficult problem that increases in importance as telecom network transition to all-packet equipment. Operators require solutions that are accurate in localization and do not impose large additional costs in terms of hardware deployment or manual labor for operations. Existing commercial solutions are generally difficult to operate, while many academic proposals typically require significant computational resources and are difficult to adapt to production networks. This paper describes a novel network fault localization algorithm based on active network measurements, probabilistic inference and change detection. The algorithm is computationally efficient for networks with thousands of nodes and requires few configuration parameters. Results obtained in a simulated environment on tree topologies show that the solution provides fast and accurate localization of performance degradations.