一种认知无线网络自适应路由优化算法

An Adaptive Routing Optimization Algorithm for Cognitive Wireless Networks

通常情况下认知无线电网络(CRN)无法直接使用一般网络的路由协议。提出在CRN中使用的一种基于粒子群优化(PSO)的自适应粒子群优化路由(APSOR)算法。APSOR算法通过对PSO方法的改进,可以处理多目标路由问题而优于列举的几种经典最短路径算法。建立并实现分布式APSOR仿真模型,在每个节点上分别计算最优路径。该算法的另一优势是这种分布式自适应算法同样考虑了在CRN路由中对QoS性能指标的满足。实验和仿真结果表明,相比经典算法,该算法可对不同QoS指标下的多跳路由进行自适应优化。

In general,cognitive wireless networks cannot directly use the routing protocols of general networks.An Adaptive Routing Algorithm Based on Particle Swarm Optimization(APSOR)used in Cognitive Wireless Networks(CRN)is proposed.The APSOR algorithm can deal with multi-objective routing problems by improving the Particle Swarm Optimization(PSO)method and is superior to several classic shortest path algorithms listed.A distributed APSOR simulation model is established,and the optimal path is calculated on each node.Another advantage of this algorithm is that the satisfaction of QoS performance in CRN routing is also considered.Experimental and simulation results show that the algorithm proposed can adaptively optimize multi-hop routing under different QoS.