Fault Localization Algorithm in Computer Networks Based on the Boolean Particle Swarm Optimization

The components of a computer network are vulnerable to a variety of faults such as a link break or node failure. In order to prevent faulty components from impeding the execution of network applications, it is very important to detect, locate and repair faulty components. Existing approaches to fault localization in communication systems use active or passive measures. Active measures involve additional traffic for network monitoring. On the other hand, the passive measures use the existing end-to-end data in the network in order to extract the necessary information and thus introduces no additional traffic in the network. In this paper, we propose an end-to-end approach that uses passive measures for fault isolation in communication networks and formulate the issue of fault isolation as an optimization problem. In fact, we used the Boolean Particle Swarm Optimization algorithm inferring the best node(s) to be tested, with the objective of minimizing the expected cost for all the faulty elements in the network. The performance of the proposed schemes is evaluated through an intensive simulation of different network scenarios.