Ad Hoc网络重采样转移概率模型下激励传播算法

Algorithm of Ad Hoc Network Excitation Propagation Under Resampling Transition Probability Model

无线多跳Ad Hoc网络的激励传播算法可以优化网络资源负载均衡,提高网络可靠性。传统的激励传播算法采用萤火虫梯度搜索定位协作激励方法,当网络节点分布为随机多跳的异构网络时,激励传播负载均衡存在效率低、准确性不高等问题。提出一种基于萤火虫群优化追踪的重采样转移概率模型下的无线多跳Ad Hoc网络激励传播算法,实现资源负载均衡,设计无线多跳Ad Hoc网络覆盖层次模型,提出萤火虫群优化追踪算法,在无线多跳Ad Hoc网络节点转移概率空间,设计重采样转移概率模型,得到多跳Ad Hoc网络激励传播系统状态估计。仿真结果得到该算法实现无线多跳Ad Hoc网络系统状态估计准确率要明显高于传统算法,估计误差的波动小,在解决蜕化的同时避免了样本贫化,资源负载均衡激励精度提升方面明显优越于其它算法,展示了算法的优越性能。

The excitation propagation algorithm for wireless multi hop Ad Hoc network can optimize cyber source load bal-ance, improve network reliability. Excitation propagation algorithm is adopted in traditional gradient search and location of firefly cooperation incentive method, when the network node distribution for heterogeneous network random multi hop, exci-tation propagation load balancing problems of low efficiency, accuracy is not high. A glowworm swarm optimization tracking resampling transfer probability model of wireless multi hop Ad Hoc networks based on excitation propagation algorithm is proposed, realize resource load balancing, cover layer model design of wireless multi hop Ad Hoc network, presents glow-worm swarm optimization tracking algorithm, the transition probability space in wireless multi hop Ad Hoc network node, design resampling transition probability model, obtained in multi hop Ad Hoc network communication system excitation state estimation. The simulation results obtained by the algorithm of wireless multi hop Ad Hoc network system state estima-tion accuracy is much higher than the traditional algorithm, the estimation error of the wave, at the same time resolve degen-eracy to avoid the sample impoverishment, resource load balancing incentive precision enhancement is superior to other al-gorithm, demonstrate the superior performance of the algorithm.