基于混沌粒子群算法的Ad Hoc网络优化研究

基于混沌理论提出了混沌粒子群算法C-PSO（chaotic particle swarm optimization）,C-PSO算法针对Ad Hoc网络提取的优化指标进行优化处理,在网络优化过程中,C-PSO算法充分利用了混沌系统的随机性、遍历性、敏感性等特性,避免了PSO算法“早熟”现象的出现,避免了陷入局部最优区,增强了全局收索能力。基于网络模拟器NS-3仿真系统对C-PSO算法和PSO算法进行了仿真实验测试,通过对丢包率、网络生命周期和网络吞吐率3个网络性能指标的对比分析和评估,结果表明C-PSO算法优于PSO算法,从而验证了C-PSO算法对Ad Hoc网络优化的有效性与可靠性。实现了对Ad Hoc网络优化。 

Research on Ad Hoc Network Optimization Based on Chaotic Particle Swarm Optimization

Chaotic particle swarm optimization (C-PSO) was proposed based on chaos theory to optimize the optimization index of Ad Hoc network.In the process of network optimization,C-PSO algorithm took full advantage of chaotic system in the randomness,ergodicity and sensitivity to avoid the "precocious" phenomenon of PSO algorithm,to avoid falling into the local optimal area,and to enhance the global collection capacity.Based on the NS-3 simulation system,the simulation results of C-PSO algorithm and PSO algorithm were tested.Through comparing and analyzing the three network performance indexes of packet loss rate,network life cycle and network throughput,the results show that C-PSO algorithm is superior to PSO algorithm,which verifies the validity and reliability of C-PSO algorithm for Ad Hoc network optimization.The algorithm can be applied to realize optimization of Ad Hoc network.