Evolutionary Computation for Quality of Service Internet Routing Optimization

Abstract. In this work, the main goal is to develop and evaluate a num-ber of optimization algorithms in the task of improving Quality of Service levels in TCP/IP based networks, by configuring the routing weights of link-state protocols such as OSPF. Since this is a complex problem, some meta-heuristics from the Evolutionary Computation arena were consid-ered, working over a mathematical model that allows for flexible cost functions, taking into account several measures of the network behavior such as network congestion and end-to-end delays. A number of exper-iments were performed, resorting to a large set of network topologies, where Evolutionary Algorithms (EAs), Differential Evolution and some common heuristic methods including local search were compared. EAs make the most promising alternative leading to solutions with an effec-tive network performance even under unfavorable scenarios