On Greedy Routing in Dynamic UAV Networks

TL;DR

This paper introduces a local observation-based greedy routing algorithm for dynamic UAV networks, avoiding costly route setup and improving efficiency over traditional methods.

Contribution

It proposes a novel distance-based greedy routing method that operates without central control or route maintenance, tailored for highly dynamic UAV environments.

Findings

Analytical bounds for hop count and delivery probability derived

Simulation confirms accuracy of analytical models

Proposed method outperforms centralized shortest path routing

Abstract

Unmanned aerial vehicles (UAVs), commonly known as drones, are becoming increasingly popular for various applications. Freely flying drones create highly dynamic environments, where conventional routing algorithms which rely on stationary network contact graphs fail to perform efficiently. Also, link establishment through exploring optimal paths using hello messages (as is used in AODV algorithm) deems extremely inefficient and costly for rapidly changing network topologies. In this paper, we present a distance-based greedy routing algorithm for UAV networks solely based on UAVs' local observations of their surrounding subnetwork. Thereby, neither a central decision maker nor a time-consuming route setup and maintenance mechanism are required. To evaluate the proposed method, we derive an analytical bound for the expected number of hops that a packet traverses. Also, we find the expected end-to-end distance traveled by each packet as well as the probability of successful delivery. The simulation results verify the accuracy of the developed analytical expressions and show considerable improvement compared to centralized shortest path routing algorithms.