Title :
Genetic and particle swarm hybrid QoS anycast routing algorithm
Author :
Li Taoshen ; Xiong Qin ; Ge Zhihui
Author_Institution :
Sch. of Comput., Guangxi Univ., Nanning, China
Abstract :
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.
Keywords :
genetic algorithms; particle swarm optimisation; quality of service; telecommunication network routing; IPv6; NP complete problem; anycast routing algorithm; communication model; genetic algorithm; hybrid algorithm; nonlinear combination optimization; particle swarm optimization algorithm; quality of service; Convergence; Educational institutions; Genetic algorithms; Genetic mutations; Iterative algorithms; Marine animals; Network servers; Particle swarm optimization; Routing; Web server; anycast routing; genetic algorithm; particle swarm optimization; quality of service(QoS);
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
DOI :
10.1109/ICICISYS.2009.5357837
