A Geographic Location Prediction-based Routing Algorithm for Flying Ad Hoc Networks

In this paper, a geographic location prediction-based routing algorithm is proposed for flying ad hoc networks. In order to reduce the impact of location inaccuracy caused by high mobility of UAVs, a Gauss distribution is used to describe the UAV movement probability density function and predict the precise location. Besides, the proposed algorithm adopts a greedy forwarding strategy based on location, considering various factors such as distance, deflection angle, velocity, direction of movement and the number of neighbors. If greedy forwarding fails, the failed node seeks its two-hop neighbors to select a node with better decision values. Simulation results show that compared with ad hoc on-demand distance vector (AODV) and greedy perimeter stateless routing (GPSR) protocols, the proposed algorithm can greatly reduce end-to-end delay and improve packet delivery rate.