FNTAR: A Future Network Topology-aware Routing protocol in UAV networks

Unmanned aerial vehicles (UAVs) can gather data in the air and transmit the data to the ground station. Multi-UAV systems have been used in an increasing number of mission scenarios and routing protocols play a critical role in UAV network communications. It is now well established that unstable link quality and frequently changing network topology pose significant challenges for messages forwarding in UAV networks. Hence, traditional mobile ad-hoc network routing protocols do not fit well in UAV networks. In many UAV applications, the flight paths of UAVs are planned in advance before performing missions. The positions and motion information of UAVs are available through Global Positioning System (GPS) and inertial sensors, which can be utilized to calculate the future positions of UAVs. Therefore, the future topology of the UAV network is also available. However, existing work does not take advantage of this information. Based on the trajectory, location and motion information of the UAVs, this paper proposes a future network topology-aware routing (FNTAR) protocol, which uses future location information to make superior routing decisions. Moreover, to mitigate data loss problems caused by unstable links and highly dynamic topology, FNTAR can forward messages to multiple excellent next-hop UAVs based on future network topology, and these UAVs can deliver messages to destinations faster. We implement FNTAR in the simulation experiment, the simulation results demonstrate that FNTAR can achieve lower latency and higher delivery ratio than DTNgeo protocol.

I. Introduction

With the advancement of electronic, sensor and communication technologies, the performance of the unmanned aerial vehicles (UAVs) system has also made great progress. Due to UAVs’ agility, easy installation, versatility and operation simplicity, they are gradually being used in various tasks, such as search and rescue missions, border surveillance, disaster monitoring and remote sensing. Multiple UAVs systems have many advantages, such as low cost, low mission completion time, better survivability and better scalability [1].