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针对航空高动态无人机(UAV)网络环境中节点移动速度快、网络拓扑变化快,导致网络链路稳定性差、数据到达率低和信息拥塞度高等问题,提出了一种航空高动态网络链路感知OLSR(OLSR-LA)路由算法,该算法利用接收的2个连续Hello消息的多普勒频移、能量等信号特征,计算出航空高动态无人机网络中2个相邻节点的相对速度和移动趋势,从而得出这2个节点之间链路的保持时间。根据节点MAC层接口队列长度衡量网络局部的负载程度,并利用ARIMA-WNN组合预测模型预测下一时刻节点负载的预测值,并通过Hello消息传递给邻居节点。根据链路感知情况,采用基于局部路由负载均衡(RRLB)算法避免拥塞的发生。仿真结果表明,与传统OLSR算法相比,本文提出的算法有效提高了分组交付率,降低了端到端的传输延时,增加了网络吞吐量,从而提高了整个无人机网络传输的有效性和实时性。
Aiming at the problems of high moving speed of node and rapid change of network topology in the UAV network environment, which leads to poor stability of network link, low data arrival rate and high congestion of information, this paper proposes an airborne high dynamic network link Road sensing OLSR (OLSR-LA) routing algorithm, the algorithm uses the received two consecutive Hello messages Doppler frequency shift, energy and other signal characteristics to calculate the aviation high dynamic UAV network in the two adjacent nodes relative Speed and moving trend, so as to draw the link holding time between the two nodes. According to the queue length of node MAC layer interface, the load degree of local network is measured, and the prediction value of node load at the next moment is predicted by ARIMA-WNN combined forecasting model, and then transmitted to neighbor nodes through Hello message. According to the link perception, the local routing load balancing (RRLB) algorithm is adopted to avoid the congestion. The simulation results show that compared with the traditional OLSR algorithm, the proposed algorithm effectively improves the packet delivery rate, reduces the end-to-end transmission delay and increases the network throughput, thus improving the effectiveness of the entire UAV network transmission and real-time.