ROUTING OPTIMIZATION STRATEGY USING GENETIC ALGORITHM

Abstract

Intelligent analysis and designing of network routing provides an edge in this increasingly fast era. In this work, a variation of Genetic Algorithm (GA) for finding the Optimized shortest path of the network is presented. The algorithm finds the optimal path by using an objective function consisting of the bandwidth and delay metrics of the network and also through bandwidth and utilization metrics. The main distinguishing element of this work is the use of “2-point over 1-point crossover”. The population comprises of all chromosomes (feasible and infeasible). Moreover, it is of variable length, so that the algorithm can perform efficiently in all scenarios. Rank-based selection is used for cross-over operation. Therefore, the best chromosomes are crossed over and give the most suitable offsprings. If the resulting offsprings are least fitted, they are discarded. Mutation operation is used for maintaining the population diversity. Various experiments have been performed for the population selection. The experiments indicate that random selection method is the most optimum. Hence, the population is selected randomly once the generation is developed. The results prove that proposed algorithm finds the optimal shortest path more efficiently than existing algorithms.