Unmanned aerial vehicle (UAV) network is widely used in environmental monitoring, target searching and rescuing, logistics, and other fields due to its characteristics of large-scale coverage, rapid deployment and strong resistance to destruction. When users are interested in sensory data in certain areas covered by UAV networks, they can send a spatio-temporal range query with time and geography constraints through the ground station. For example, obtaining the temperature information around fire points in the forest within an hour before the fire bursts out. Then, UAVs that carry the query results will return the data to the ground station through multi-hop routing. However, most of the existing spatio-temporal range query algorithms are designed for static networks. How to conduct spatio-temporal range queries in the UAV networks is still an open problem. In this paper, we propose a Trajectory-Aware Spatio-Temporal range query processing algorithm (TAST) for UAV networks. The ground station takes advantage of the pre-planned trajectory information of UAVs to build the topology change model of the UAV network, which can reflect the changes of UAVs’ communication links and neighbors. Furthermore, the static topology change graph (TCG) is proposed for optimizing the routing of query results in the spatio-temporal query processing. Next, we propose a Trajectory-Aware Spatio-Temporal range query processing algorithm based on packet Splitting (TASTS), which is used to split large query results into multiple small packets called unit packets, and each unit packet is transmitted back to the ground station independently and efficiently. Finally, we evaluated our algorithms through simulation experiments. The simulation results show that TAST and TASTS perform well in terms of query success rate, query efficiency and overhead ratio.

无人机（UAV）网络以其覆盖范围大、部署迅速、抗破坏能力强等特点，被广泛应用于环境监测、目标搜救、物流等领域。当用户对无人机网络覆盖的某些区域的传感数据感兴趣时，他们可以通过地面站发送具有时间和地理限制的时空范围查询。例如，在火灾发生前一小时内获取森林中火点周围的温度信息。然后，携带查询结果的无人机将通过多跳路由将数据返回给地面站。然而，现有的大多数时空范围查询算法都是为静态网络设计的。如何在无人机网络中进行时空范围查询仍然是一个悬而未决的问题。在本文中，我们提出了一种用于无人机网络的轨迹感知时空范围查询处理算法（TAST）。地面站利用无人机预先规划的轨迹信息构建无人机网络拓扑变化模型，可以反映无人机通信链路和邻居的变化。此外，为了优化时空查询处理中查询结果的路由，提出了静态拓扑变化图（TCG）。接下来，我们提出了一种基于包拆分（TASTS）的轨迹感知时空范围查询处理算法，用于将大查询结果拆分为多个称为单元包的小包，每个单元包独立高效地传回地面站。最后，我们通过模拟实验评估了我们的算法。仿真结果表明，TAST和TASTS在查询成功率、查询效率和开销比方面表现良好。