摘要
无人机(Unmanned Aerial Vehicle,UAV)集群凭借其高度自主性、高速机动性和强环境适应能力,使网络拓扑结构呈现动态时变特性,因此能量消耗问题成为制约网络可持续运行的核心瓶颈。为缓解无人机群网络能量消耗不均衡的问题,提出基于空间分布式协调功能(Spatial Distributed Coordination Function,S-DCF)算法的无人机群临时(Ad Hoc)网络节点布局能耗优化方案。定义节点剩余能量权重系数,融合节点地理中心度指标,构建多目标综合选举函数,实现网络分簇。针对簇内节点,采用改进的S-DCF协议,通过簇头节点协调的时隙分配机制有效降低数据冲突概率。以网络总能耗最小化作为优化目标,结合粒子群优化算法实现网络节点布局能耗优化。测试结果表明,采用所提方法可使无人机节点能耗降低21.6%~25.3%(均值接近24%)。所提方法在保持目标区域高覆盖率的同时,显著提升了网络能效。
Unmanned aerial vehicle(UAV)cluster with high degree of autonomy,high-speed mobility and strong environmental adaptability,result in a dynamic and time-varying network topology,and energy consumption issues become a core bottleneck that restricts the sustainable operation of the network.In order to alleviate the problem of uneven energy consumption in the UAV cluster network,an energy consumption optimization of the UAV cluster Ad Hoc network node layout based on the spatial distributed coordination function(S-DCF)algorithm is proposed.The residual energy weight coefficient of nodes is defined,and the geographic centrality index of nodes is fused to construct a multi-objective comprehensive election function to realize network clustering.The improved S-DCF protocol is adopted for the nodes in the cluster,and the data conflict probability is effectively reduced through the slot allocation mechanism of cluster head node coordination.The optimization goal is to minimize the total energy consumption of the network,and the energy consumption optimization of the network node layout is realized by combining particle swarm optimization(PSO)algorithm.The test results show that the proposed method can reduce the energy consumption of UAV nodes by 21.6%~25.3%(the average is close to 24%).The proposed method not only maintains the high coverage of the target area,but also signifi-cantly improves the network energy efficiency.
作者
段昌盛
DUAN Changsheng(School of Information Engineering,Enshi Polytechnic,Enshi 445000,China)
出处
《测控技术》
2025年第8期56-61,共6页
Measurement & Control Technology
基金
教育部职业教育发展中心2024年职业教育理论与实践研究支持课题(JZZC25008)。
