Topology control algorithms in multi-unmanned aerial vehicle networks: An extensive survey

• Published in: Journal of network and computer applications 2022-11, Vol.207, p.103495, Article 103495
• Main Authors: Alam, Muhammad Morshed, Arafat, Muhammad Yeasir, Moh, Sangman, Shen, Jian
• Format: Article
• Language: English
• Subjects: Clustering; Collision avoidance; Connectivity control; Coverage control; Flocking control; Flying ad hoc network; Swarm intelligence; Topology control algorithm; Unmanned aerial vehicle network
• ISSN: 1084-8045; 1095-8592
• DOI: 10.1016/j.jnca.2022.103495

In recent years, unmanned aerial vehicles (UAVs) have attracted increased attention from academic and industrial research communities, owing to their wide range of potential applications in military and civilian domains. A collaborative group of UAVs operating in an ad hoc manner known as a flying ad hoc network (FANET) can accomplish complex tasks more efficiently. However, owing to the high mobility of UAVs, such applications remain limited by a few key challenges, including dynamic time-varying topologies, energy constraints, frequent link breakages, inter-UAV collisions, and external obstacle avoidance. A proper topology control algorithm (TCA) for UAV swarms with reasonable overhead helps to optimize both mission and communication performance in FANET. Thus, TCA provides wider coverage ensuring the quality of service in aerial connectivity. Additionally, it supports the efficient energy management, better target exploration, improved formation stability while ensuring inter-UAV collision avoidance, external obstacle avoidance, lower interference, and the enhanced autonomy of UAV swarms. In this article, we present a comprehensive survey of available TCAs for FANET, and provide a novel taxonomy of TCAs based on the FANET topology architectures and underlying mathematical models. Through an in-depth assessment of recent innovative research articles and their comparative studies, we aim to provide novel insights into the latest technologies for autonomous cooperative coordination. The key open research issues and their respective solutions are addressed as future research directions.