Reliability Evaluation of Communication Networks

Abstract

In the evaluation of the capacity of a communication network architecture to resist to the possible faults of some of its components, several reliability metrics are currently used. The evaluation of these metrics is in general a very costly task since most of them are, as algorithmic problems, classed in the NP-hard family. As a consequence, many different techniques have been proposed to solve them. We discuss here a promising class of methods called “factorization” and some of the implementation issues. An alternative approach to these exact techniques is to perform statistical estimations using a Monte Carlo simulation. It allows to deal with larger networks (having, say, hundreds of components) if the user accepts probabilistic answers. In the case of highly reliable networks, the standard Monte Carlo technique is also prohibitively expensive and variance reduction techniques must be used. We propose here a new Monte Carlo algorithm specifically designed to this context. For both approaches, exact and simulation algorithms, numerical results are provided allowing a comparison and giving an idea of the performances that can be expected.