A scheduling-based event correlation scheme for fault identification in communications network

Abstract

Communications network has increased dramatically in size and complexity in the past few years. A typical network may consist of hundreds of nodes from various manufacturers with different traffic and bandwidth requirements. The increasing complexity poses serious problems to network management and control. As faults are inevitable, quick detection, identification and recovery are crucial to make the systems more robust and their operation more reliable. This article proposes a novel event correlation scheme for fault identification in communications network. This scheme is based on the bi-level feedback queues scheduling policy. The causality graph model is used to describe the cause-and-effect relationships between network events. The use of scheduling policy makes the correlation process simple and fast. A simulation model is developed to verify the effectiveness and efficiency of the proposed scheme. From simulation results, we notice that this scheme not only identifies multiple problems at one time but also is insensitive to noise. As the time complexity of the correlation procedure is close to a function of n, where n is the number of observed symptoms, with order O(n); therefore, the on-line fault identification is easy to achieve.