基于路径规划的无人机加权高效分簇方法  

UAV Weighted Efficient Clustering Method Based on Path-planning

作　　者：严磊 雷磊[1] 蔡圣所[1] 路志勇[2] YAN Lei;LEI Lei;CAI Shengsuo;LU Zhiyong(College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;The 54th Research Institute of China Electronics Technology Group Corporation,Shijiazhuang 050081,China)

机构地区：[1]南京航空航天大学电子信息工程学院,南京210016 [2]中国电子科技集团公司第五十四研究所,石家庄050081

出　　处：《计算机工程》2018年第11期276-281,共6页Computer Engineering

基　　金：国家自然科学基金(61572254);江苏省自然科学基金(BK20161488);航空科学基金(2016ZC52029)

摘　　要：分簇是延长无人机编队网络生存时间、增强网络抗毁性和可扩展性的重要手段。结合无人机路径规划策略,提出2种无人机编队网络加权高效分簇方法,即基于路径规划的簇首加权选举算法(WHEA-P)和基于路径规划的簇成员加权调整算法(WCAA-P)。2种算法充分考虑了在路径规划条件下无人机编队网络拓扑变化对分簇结构的影响,分别在簇首选举阶段和簇成员调整阶段实现了无人机编队网络分簇的动态调整。仿真实验结果表明,2种算法均能有效地实现网络负载均衡,降低节点能耗,延长网络生存时间,性能明显优于典型的最小ID号分簇算法和加权分簇算法。UAV clustering is an important means to prolong network lifetime and enhance the survivability and the scalability of the network.Based on path-planning,two weighted efficient clustering algorithms for UAV network are proposed,which are Weighted Head Election Algorithm based on Path-planning(WHEA-P)and Weighted Cluster Adjustment Algorithm based on Path-planning(WCAA-P).These two algorithms take full account of the influence of network topology change on cluster structure with the help of UAV path-planning,and dynamically adjust the cluster of networks in the cluster head election phase and the cluster member adjustment phase respectively.The results show that two proposed algorithms perform better than the least ID algorithm and the weighted clustering algorithm,and can effectively balance the load of nodes.Thus it reduces energy consumption of the nodes and prolongs network lifetime.

关 键 词：无人机分簇 路径规划 簇首选举 簇成员调整 网络生存周期 负载均衡 

分 类 号：TP872[自动化与计算机技术—检测技术与自动化装置]