Genetic algorithms for designing multihop lightwave network topologies

Abstract

Multihop lightwave networks are a means of utilizing the large bandwidth of optical fibers. In these networks, each node has a fixed number of transmitters and receivers connected to a common optical medium. A multihop topology is implemented logically by assigning different wavelengths to pairs of transmitters and receivers. By using tunable lasers or receivers, it is possible to modify the topology dynamically when node failures occur or traffic loads change. The reconfigurability of logical multihop lightwave networks requires that optimal topologies and flow assignments be found. In this article, optimization of these logical topologies by genetic algorithms is investigated. The genetic algorithm takes topologies as individuals of its population, and tries to find optimal ones by mating, mutating and eliminating them. During the evolution of solutions, minimum hop routing with flow deviation is used to assign flows, and evaluate the fitness of topologies. The algorithm is tested with different sets of parameters and types of traffic matrices and the solutions are compared against histograms of random samples from the solution space. These tests show that the solutions found by the genetic algorithm are comparable with and in some cases better than those found by existing heuristic algorithms.