Novel DTN Mobility-Driven Routing in Autonomous Drone Logistics Networks

Abstract

Drones have become prevalent for the delivery of goods by many retail companies such as Amazon and Dominos. Amazon has an issued patent that describes how drones scan and collect data on their fly-overs while dropping off packages. In this context, we propose a path optimization algorithm for a drone multi-hop communications network that can carry and forward data in addition to its primary function of parcel deliveries. We argue that traditional Delay Tolerant Networking (DTN) based protocols may not be efficient for this purpose. Therefore, this paper proposes a new DTN-based algorithm that optimizes drone flight paths in conjunction with optimized routing to deliver both parcels and data in a power efficient way and within the shortest possible time. We propose a heuristic algorithm called Weighted Flight Path Planning (WFPP) that priorities the data packets in an exchange pool in order to create an optimized path for the drones. Our approach is to determine a weight for each packet based on the packet's remaining time to live, priority, size, and location of the packet's destination. When two drones meet each other, they exchange the high weighted packets. Simulation studies show that WFPP delivers up to 25% more packets compared with EBR, EPIDEMIC, and a similar path planning method. Also, WFPP reduces the data delivery delays by up to 66% while the overhead ratio is low.