Load balancing in IP networks by optimising link weights

We present a hybrid genetic algorithm (GA) approach to optimise link weights used for routing inside an autonomous system in IP networks. This method can be seen as an alternative to metaheuristic-based approaches previously proposed in the literature. However, our approach is based on a simple but powerful GA, which utilises a plain but flexible objective function, taking both maximum link utilisation and weight reconfiguration into account. Furthermore, the population-based feature of the GA is enhanced with a search heuristic representing an individual-based search method to form a hybrid GA (HGA). We demonstrate our method in a case of a small network and compare the results with the linear programming (LP) lower bound of general optimal routing. Afterwards we show the results for a bigger network with increasing traffic demands, compared with the results of some conventional weight settings as well as with the LP lower bound. Copyright (c) 2005 AEIT.