Loading...
Kommu Kishore Babu is an Assistant Professor in the Department of Computer Science and Engineering at Vignan’s Foundation for Science, Technology and Research, India. His contribution focuses on Artificial Intelligence, Software-Defined Networking, and network optimization.
Software-Defined Networking (SDN) is a network framework that distinguishes the control plane from the data plane, facilitating centralised, programmable, and adaptable network administration. The expanding magnitude and intricacy of contemporary networks, such as cloud infrastructures, data centers, 5G/6G frameworks, Internet of Things (IoT) ecosystems, and edge networks, have necessitated intelligent network administration. Artificial Intelligence (AI) and Machine Learning (ML) can improve Software-Defined Networking (SDN) through automated traffic forecasting, routing enhancement, congestion control, resource distribution, anomaly identification, quality-of-service (QoS) refinement, and security oversight. This chapter delineates the principles of Software-Defined Networking (SDN), the architecture of AI-enhanced SDN, machine learning methodologies for network enhancement, intelligent routing, traffic management, resource distribution, congestion forecasting, security implementations, reinforcement learning, deep learning, edge intelligence, performance indicators, obstacles, and prospective research avenues. The amalgamation of AI and SDN establishes a basis for autonomous and self-optimizing networks that can fluidly adjust to fluctuating traffic patterns and application demands.