DroneNet+: Adaptive Route Recovery Using Path Stitching of UAVs in Ad-Hoc Networks

In this paper, we consider a route recovery problem using Unmanned Aerial Vehicles (UAVs) as relay nodes to connect with terrestrial ad-hoc networks in realistic disaster scenarios. Our main goal is to perform network probing from the air by UAVs and find out crucial spots where both local and global routing performance can significantly be recovered if they are deployed. We propose a route topology discovery scheme that extracts the inherent route skeletons by stitching partial local paths obtained from simple packet probing by UAVs, while exploring a designated Region of Interest (RoI) by an adaptive traversing scheme. By leveraging the captured topology, we dispatch a limited number of UAVs by an iterative UAV deployment algorithm and provide a lightweight yet effective network hole replacement decision in a heuristic manner. Simulation results demonstrate that our traversing algorithm reduces the complete coverage time, the travel distance, and the duplicate coverage compared to a previous work, DroneNet. Our subsequent iterative deployment algorithm greatly recovers severely impaired routes in a damaged network, while substantially reducing computational complexity.