链路预测模型下的无人机网关选择算法

针对无人机自组网和地面控制站通信时网关节点持续时间短并由此带来的数据传输时延过大和成功率不高等问题,提出了一种基于无人机-地面控制站链路状态预测的网关选择算法.该算法通过建立基于无人机活动模型的预测和基于无人机运动趋势的预测,从而选择与地面控制站连接时间较长的节点作为网关候选节点.此外,通过使用函数计时机制选择网关选择参数最大的节点作为网关节点,有效避免分布式网关选择算法中随机延迟机制导致的不必要的网关切换.仿真结果表明,与现有的无人机分布式网关选择算法和移动自组网分簇算法相比,该算法有效延长了网关节点持续工作时间,并使无人机网络与地面控制站通信时的数据传输时延、数据传输成功率等性能得到提升.

UAV Gateway Selection Algorithm Under Link Prediction Model

For improving large delay of data transmission and low rate of data success transmishort duration of the gateway node when the unmanned aerial vehicle( UAV) Ad Hoc networks communicates with the ground control station( GCS),a gateway selection algorithm based on UAV-GCS link state prediction is proposed. The proposed algorithm selects the nodes with longer time connection with the GCS by establishing the prediction based on the UAV activity model and motion trend. In addition,the node with the largest gateway selection parameter becomes the gateway node by adopting the function timing mechanism. That can avoid unnecessary gateway handoff caused by non-optimal parameters of the selected gateway. The simulation results show that the proposed algorithm effectively extends the working time of gateway nodes and has the advantages of longer average duration of the gateway node,smaller data transmission delay and higher rate of data success transmission,compared with the existing distributed gateway selection algorithm of the unmanned aerial vehicle and the mobile ad hoc network clustering algorithm.