Genetic-algorithm-based reliability optimization for computer network expansion

Abstract

This paper explains the development and implementation of a new methodology for expanding existing computer networks. Expansion is achieved by adding new communication links and computer nodes such that reliability measures of the network are optimized within specified constraints. A genetic algorithm-based computer network expansion methodology (GANE) is developed to optimize a specified objective function (reliability measure) under a given set of network constraints. This technique is very powerful because the same approach can be extended to solve different types of problems; the only modification required is the objective function evaluation module. The versatility of the genetic algorithm is illustrated by applying it to solve various network expansion problems (optimize diameter, average distance and computer network reliability for network expansion). The results are compared with the optimal solutions computed using an exhaustive search of complete solution space. The results demonstrate that GANE is very effective (in both accuracy and computation time) and applies to a wide range of problems, but it does not guarantee the optimal results for every problem. >