Exploring optimal resource allocation methods for improved efficiency in flying ad-hoc network environments: a survey

Abstract

This survey explores optimal resource allocation methods to enhance the efficiency of flying ad-hoc networks (FANETs). Unmanned aerial vehicles (UAVs), commonly known as drones, are widely deployed in military and civilian applications, necessitating effective coordination and communication to overcome challenges. FANETs facilitate wireless communication among UAVs, improving coordination and information exchange in environments lacking traditional networks. The dynamic mobility of UAVs introduces unique considerations for network design and connectivity, distinguishing FANETs from conventional ad-hoc networks. This survey reviews various optimization techniques, including genetic algorithms, ant colony optimization, and artificial neural networks, which optimize resource allocation by considering mission requirements, network topology, and energy constraints. The paper also discusses the critical role of intelligent algorithms in enhancing network energy management, quality of service (QoS), maximizing resource allocation, and optimizing overall performance. The systematic literature review categorizes resource allocation strategies based on performance optimization criteria and summarizes their strengths, weaknesses, and applications. This survey highlights the potential of FANETs to revolutionize various industries and unlock new opportunities for UAV-based applications.