An adaptive particle swarm optimization algorithm for anycast routing

作者：Li Taoshen^*; Zhao Zhigang; Ge Zhihui

来源：Journal of Computational Information Systems, 2011, 7(5): 1559-1566.

• Adaptive particle swarm optimization algorithm
• Anycast
• Anycast routing
• Communication mode
• Convergence rates
• Convergence velocity
• Evolutionary equation
• Inertia weight
• Local optima
• Multiple QoS
• Mutation operators
• Network load
• Network resource
• Nonlinear combination
• NP complete problems
• Particle swarm
• Particle swarm optimization algorithm
• QoS constraints
• Running time
• Simulation experiments

Anycast is a new communication mode proposed in IPv6. The anycast routing problem with multiple QoS parameters constrained is a nonlinear combination optimization problem, which is proved to be a NP complete problem. The particle swarm optimization algorithm that has slow convergence rate in the later period is easily trapping in local optimum and low convergence precision has been improved. On the base of the simplified evolutionary equations, an adaptive particle swarm optimization algorithm for anycast routing with QoS constraints is proposed to optimize network resource and balance network load. This applies some methods such as dynamically changing the inertia weight and introducing the mutation operator during the running time. The simulation experiments show that the algorithm is feasible and effective in anycast routing. It can effectively break away from the local optimum and improve the convergence velocity extraordinarily.

• 出版日期2011
• 单位广西大学