Efficient fault localization using active diagnosis risk modeling and fault management in communication networks

Abstract

Todays Internet backbone networks offer enhanced performance to overcome loss delay and unavailability However in the event of a problem in a network component the network experiences failures such as link faults path faults and router failures An efficient automated fault localization methodology is necessary to identify faults in the network Faults may occur in a higher or lower network layer Internet Protocol IP networks are constructed with point to point links between different routers overlaying the underlying optical topology The exact root cause of failures needs to be detected To achieve the promise of fault localization effective and efficient automated active diagnosis risk modeling is fundamental to the operations of an ISP backbone network Given the complex nature of the IP network new and efficient fault localization techniques that detect faults without undue delay are called for Each shared risk is associated with a set of observations according to the risk model and represented as a bipartite graph This set cover problem is Non deterministic Polynomial NP time hard so the greedy approximation can find an approximate solution This is a promising method for fault localization since it is possible to locate faults in reasonably quick time In this dissertation the proposed Shared Risk Greedy Algorithm SRGA approach applied for fault localization problems helps identify the location of a fault by employing the greedy heuristic approach The SRGA is a flexible and robust heuristic method for fault localization It maps failure signature identification at higher layers and determines possible causes of lower layer failures executed by the risk model This mapping includes failures brought on by optical components and other shared components It achieves a high level of problem solving efficacy for the IP network newline