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为提高长链树状无线传感器网络的服务质量(QoS),本文用云遗传蚁群网络算法对无线传感器网络路由进行优化.算法中将正向蚂蚁根据节点负载情况发现的可行路径作为遗传算法的初始种群进行染色体编码,用路径时延、跳数及链路质量定义的适应度函数对染色体进行评价;利用正态云发生器实现路径的交叉和变异操作,逆向蚂蚁对优化后的路径进行信息素更新.仿真结果表明该路由算法能够满足无线传感器网络的实时性、可靠性等方面的要求,实现了网络的负载平衡及拥塞控制机制.
In order to improve the quality of service (QoS) of long-chain tree-like WSNs, this paper uses the cloud-based ant colony algorithm to optimize the routing of wireless sensor networks. The algorithm uses the feasible path found by the ant based on the node load as the genetic algorithm Chromosome coding was performed on the initial population. Chromosomes were evaluated using fitness functions defined by path delays, hop counts, and link quality. Crossing and mutation operations were performed using a normal cloud generator. Reverse ants performed information on the optimized path The results of the simulation show that the routing algorithm can meet the requirements of real-time and reliability of wireless sensor networks, and achieve the network load balancing and congestion control mechanism.