Article Open Access

A Position-based Hybrid Routing Protocol for Clustered Flying Ad Hoc Networks

Drones and Autonomous Vehicles. 2024, 1(1), 10001; https://doi.org/10.35534/dav.2024.10001
Godwin Asaamoning 1, 2, *    Paulo Mendes 3,   
1
Liberal Studies Department, Bolgatanga Technical University, Sumbrungu UB-0964-8505, Ghana
2
COPELABS, Universidade Lusofona, 1749-024 Lisbon, Portugal
3
Airbus Central Research and Technology, Taufkirchen, 82024 Munich, Germany
*
Authors to whom correspondence should be addressed.

Received: 15 Sep 2023    Accepted: 10 Jan 2024    Published: 16 Jan 2024   

Abstract

Unmanned aerial vehicles (UAVs) have been used to establish flying ad hoc networks (FANETs) to support wireless communication in various scenarios, from disaster situations to wireless coverage extensions. However, the operation of FANETs faces mobility, wireless network variations and topology challenges. Conventional mobile ad hoc network and vehicular ad hoc network routing concepts have rarely been applied to FANETs, and even then they have produced unsatisfactory performance due to additional challenges not found in such networks. For instance, position-based routing protocols have been applied in FANET, but have failed to achieve adequate performance in large networks. Clustering solutions have also been used in large networks, but with a significant overhead in keeping track of the complete topology. Hence, to solve this problem, we propose a hybrid position-based segment-by-segment routing mechanism for clustered FANETs. This approach facilitates traffic engineering across multiple wireless clusters by combining position-based inter-cluster routing with a rank-based intra-cluster routing approach capable of balancing traffic loads between alternative cluster heads. Simulation results show that our solution achieves, on average, a lower power consumption of 72.5 J, a higher throughput of 275 Mbps and a much lower routing overhead of 17.5% when compared to other state-of-the-art end-to-end routing approaches.
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© 2024 by the authors; licensee SCIEPublish, SCISCAN co. Ltd. This article is an open access article distributed under the CC BY license (https://creativecommons.org/licenses/by/4.0/).