Boids Swarm-based UAV Networking and Adaptive Routing Schemes for Emergency Communication

Communications in disaster scenarios face critical challenges because of damage to ground communication facilities. A promising solution for emergency response is establishing self-organizing networks with flexible unmanned aerial vehicles (UAVs) swarms to provide a communication guarantee for rescue mission execution. However, the server environment of the disaster area and the highly dynamic characteristic of UAV networks place strict requirements on swarm mobility control and data transmission. To this end, this work proposes a Boids mobility model-based adaptive routing scheme to achieve efficient UAV swarm networking. Specifically, we develop a biological-inspired Boids-based Social Force Model (BSFM) to implement swarm mobility control with location information and link states to improve the communication performance of UAV networks. Then, we design an adaptive routing scheme to adjust the Hello message sending interval based on the relative velocity and distance between the UAV s for neighbor discovery and topology maintenance. We conduct experiments with Network Simulator 3 (NS-3) for performance evaluation, and simulation results show that our method outperforms conventional approaches regarding the average delay, packet loss ratio, and network throughput.