无线传感器网络路径寻优的仿真研究

摘要

Study wireless sensor network path optimization problems. In order to solve the problems of slow convergence speed of genetic algorithm and easy getting into the local optimum in sensor network path optimization, the article puts forward a taboo genetic algorithm path optimization method. By using genetic algorithm global optimization, the algorithm firstly makes the optimal paths be stably distributed in the solution space, the by adopting taboo algorithm local searching is carried out to overcame the defect of slow convergence speed of genetic algorithm. Simulation results show that this algorithm can find the optimal wireless sensor network and improve the quality, and the optimal rate also be improved, which can effectively realize the network load balance and extend the network lifetime.%研究无线传感器网络路径寻优问题.针对无线传感器网络路径寻优同时涉及到数据传输路径的长度、传感器节点能量以及整个网络的能量均量均衡,传统的数学模型对其进行求解存在求解时间长,速度慢,得到的路径并非最优,导致网络的能量不均衡,网络生命周期短.为了快速找到传感器网络最优路径,提出一种传感器路径混合寻优方法.算法首先利用遗传算法进行全局寻优,使网络最优路径稳定地分布在解空间区域,然后采用禁忌算法进行网络路径局部寻优,最后找到无线传感器最优路径.仿真结果表明,混合算法能快速找到无线传感器网络最优路径,且消耗的能量最少,有效实现了网络负载均衡,延长了网络的生命周期.