5G背景下智慧农业通信节点部署策略

A Deployment Strategy for Communication Nodes of Intelligent Agriculture Under 5G Background

针对5G背景下大规模智慧农业传感器网络通信节点在三维空间内部署时,传统的随机节点部署方式存在高能耗、高成本及节点脱节问题,提出了一种基于维诺图(VD)与飞蛾扑火算法(MFO)结合的节点优化部署策略。首先,利用5G通信高带宽的特点,设计了一种分层式通信方案,在此基础上,建立了分层式节点最优部署模型、通信能耗模型以及传感器信息传输网络全连通模型;其次,针对MFO算法种群生成的随机性及搜索无向性的缺陷,设计了基于三维VD的引导式搜索算法(VIMFO);最后,通过对相关模型进行优化求解,从而取得传感器网络通信节点的部署位置。仿真结果表明,与经典MFO算法相比,VIMFO算法能够在提升寻优速度37.89%的基础上,降低传感器通信网络能耗6.9%;在保证农田传感器通信网络节点全连通的前提下,提升了通信网络节点的生存周期。

A node optimal deployment strategy based on the combination of Voronoi diagram(VD)and moth flame optimization(MFO)algorithm is proposed to solve the problems of high energy consumption,high cost and node disconnection existing in the traditional random deployment of large-scale intelligent agricultural sensor network communication nodes in 3D space under the background of 5G.Firstly,a hierarchical communication scheme is designed based on the high bandwidth of 5G communication.Then,an optimal deployment model of hierarchical nodes,a communication energy consumption model and a full connectivity model of sensor information transmission network are established.Secondly,a guided search algorithm(VIMFO)based on 3D VD is designed to overcome the defects of MFO in the randomness of population generation and search undirectivity.Finally,the deployment location of communication nodes in sensor networks is obtained by optimizing the relevant models.Simulation results and a comparison with the classical MFO algorithm show that the proposed algorithm improves the optimization speed by 37.89%,and reduces the energy consumption of sensor communication network by 6.9%,and that the lifetime of communication network nodes is improved on the premise of ensuring the full connectivity of farmland sensor communication network nodes.