Genetic and particle swarm hybrid QoS anycast routing algorithm

Anycast is proposed in IPv6 as a new communication model and becoming increasingly important. Anycast refers to the transmission of data from a source node to (any) one member in the group of designed recipients in a network. The QoS anycast routing problem is a nonlinear combination optimization problem, which is proved to be a NP complete problem. A hybrid algorithm which combines genetic algorithm and particle swarm optimization algorithm is proposed to solve anycast routing problem with multiple QoS constraints. The algorithm uses an update operator to solve the problem which the routing paths can learn from other bester paths, so that whole population tends to the best path progressively. The simulation results show that our algorithm can overcome the disadvantages of genetic algorithm and particle swarm optimization algorithm, and achieve better QoS performance. It has faster convergence speed and can escape from local optimum.