无人机通信网络非等间距节点负载部署方法

Load Deployment Method for Unequally Spaced Nodes in UAV Communication Network

针对无人机通信网络吞吐率和缓存资源利用率较低的问题,提出一种无人机通信网络非等间距节点负载部署方法。优先构建无人机通信系统节能负载的大数据挖掘模型,通过模糊特征检测方法对节点负载特征进行挖掘和优化提取。在无人机通信网络区域内.将K-均值聚类算法和粒子群算法相结合,形成多个初始粒子群.搜索最优分簇.实现无人机通信网络非等间距节点负载部署。仿真实验结果表明,所提方法可以有效增加吞吐率和缓存资源利用率,同时还能够降低通信冲突率和节点负载耗时。

Aiming at the low throughput and cache resource utilization of UAV Communication Network,a load deployment method of non-equidistant nodes in UAV Communication Network is proposed.The big data mining model of energy-saving load of UAV Communication system is constructed first,and the node load characteristics are mined and optimized by fuzzy feature detection method.In the area of UAV Communication Network,K-means clustering algorithm and particle swarm optimization algorithm are combined to form multiple initial particle swarm optimization,search the optimal clustering,and realize the load deployment of non-equidistant nodes in UAV Communication Network.Simulation results show that the proposed method can effectively increase the throughput and cache resource utilization,and reduce the communication conflict rate and node load time-consuming.