基于遗传感知优化算法的无线传感网络资源分配研究

Research on Resource Allocation of Wireless Sensor Networks Based on Genetic Sensing Optimization Algorithm

针对现有WSNs(Wireless Sensor Networks)节点资源分配算法存在的网络资源利用率低、能耗消耗过快等问题,提出一种基于优化遗传感知的网络资源分配算法。根据随机部署节点的位置、剩余能耗等,选择最佳目标节点并构建合理的网络节点拓扑结构;建立节点感知优化模型,对经典GA(Genetic Algorithm)算法进行优化,提升GA算法的大规模数据处理能力和迭代寻优能力,并将感知结果汇总到数据融合中心;为个体遗传基因选择合适的个体适应度函数,再经过编码、繁殖与交叉变异,优选出最优的节点通信链路和传感网络资源分配路径。仿真结果显示:GA算法下的节点缓存能力和带宽利用率均较高,通过节点资源合理分配可以减少能耗,并延长网络寿命。

Aiming at the problems of low utilization of network resources and too fast consumption of energy in existing WSNs node resource allocation algorithms,a network resource allocation algorithm based on optimized genetic perception is proposed.First,according to the location of the randomly deployed nodes and the remaining energy consumption,the best target node is selected and a reasonable network node topology is constructed.Secondly,a structure perception optimization model is established to optimize the classical GA algorithm,improve the data processing ability and iterative optimization ability of the GA algorithm,and summarize the perception results to the fusion center.finally,the appropriate individual fitness function is selected for individual genetic genes,and then the optimal node communication link and sensor network resource allocation path is selected through coding,breeding and cross mutation.The simulation results show that the caching capacity and bandwidth utilization rate of the node under the genetic sensing algorithm are both high,and the energy consumption loss can be reduced and the network life can be extended through reasonable allocation of node resources.