Application of genetic algorithms to VOD network topology optimization

In this paper, we point out an architecture optimization problem for networks delivering services such as Video-On-Demand or, more precisely, two intertwined problems, i.e., the storage allocation of the videos among the storage nodes of the network and the choice of the network topology. We present and investigate the properties of a genetic algorithm which can handle such problems. This algorithm, as well as a greedy heuristics and simulated annealing, are then used to derive solutions in function of link and node cost parameters in a 36-node network. The results show that genetic algorithms are an effective class of algorithms for such problems, and possibly many other topology optimization problems.