异步粒子群优化算法在QoS组播路由中的应用

Application of asynchronous pattern PSO in QoS multicast routing

QoS组播路由问题是一个非线性的组合优化问题,已证明了该问题是NP完全问题。为适应下一代IP网络对实时信息传输的要求,在异步模式粒子群优化算法基础上,给出包含延迟、延迟抖动、带宽、丢包率和最小花费5个约束条件在内的QoS组播路由算法。该算法首先给出数学模型,设计适应度函数,再给出受限的网络模型,通过粒子群优化(PSO)算法最大化适应度函数来求解最优Steiner树。算法仿真实验结果表明:与遗传算法和同步模式的粒子群优化算法相比,该算法有较好的收敛速度和寻优效果。

QoS muhicast routing problem is a nonlinear combination optimization problem,which is proved to be a NP complete problem. In order to fulfill the characteristics of real-time information transmission in next generation internet,a new quality of service（QoS） multicast routing algorithm based on asynchronous pattern particle swarm optimization（PSO） algorithm is proposed. It contains delay,delay jitter,bandwidth,packet loss and the least cost constraints. Network topology graph and fitness function are generated and designed first; secondly, restricted network model is put forward and PSO maximize fitness function is used to get the optimized Steiner tree. Simulation results show that the algorithm gives the better operation effect and the faster speed of convergence with compare to genetic algorithm and synchronous pattern PSO algorithm.