A systematic and comprehensive survey of load balancing techniques in Software Defined Network based Internet of Things

Software-Defined Networking (SDN) has become an innovative approach for managing wide-area networks, offering significant benefits through centralised management and programmability. The rapid increase in devices linked to Internet of Things (IoT) networks has produced and collected abundant data. IoT devices, characterised by their diversity and rapid expansion, pose unique challenges in complexity, management, and load balancing. Consequently, innovative approaches are required for effective IoT design and management. Integrating SDN with the Internet of Things (IoT) reshapes traditional network architectures by enabling dynamic resource allocation, improving scalability, and enhancing intelligent traffic management. This convergence also optimises load balancing, ensuring efficient network performance in diverse IoT environments. This paper offers an indepth review of various algorithms, implemented in the SDN-IoT domain, emphasizing their role in improving load balancing. It examines various phases of load balancing in SDN-based IoT networks evaluates the performance of different algorithms and highlights the key factors such as energy efficiency, traffic management and routing that produce the most effective outcomes. Furthermore, the study provides insights into how SDN-driven solutions enhance IoT network scalability, reliability, and adaptability, reinforcing the integration between SDN and IoT. The paper also presents a comparative analysis of existing research, highlighting key trends and potential future directions, making it a valuable resource for researchers in this domain.