Empowering UAV Communications with AI-Assisted Software-Defined Networks: A Review on Performance, Security, and Efficiency

Abstract

Intelligent software-defined network (SDN) in unmanned aerial vehicles (UAVs) is an emerging research area to enhance UAV communication networks’ performance, security, and efficiency. By incorporating artificial intelligence (AI) and machine learning (ML) algorithms, SDN-based UAV networks enable real-time decision-making, proactive network management, and dynamic resource allocation. These advancements improve network performance, reduce latency, and enhance network efficiency. Moreover, AI-based security mechanisms can swiftly detect and mitigate potential threats, bolstering UAV networks’ overall security. Integrating intelligent SDN in UAVs holds tremendous potential for revolutionizing the UAV communication and networking field. This paper comprehensively discusses the solutions available for UAV-based intelligent SDNs. It provides an in-depth exploration of UAVs and SDNs and presents a comprehensive analysis of the evolution from traditional networking environments to UAV-based SDN environments. Our research primarily focuses on UAV communication’s performance, security, latency, and efficiency. It includes a taxonomy, comparison, and analysis of existing ML solutions specifically designed for UAV-based SDNs.