In response to the escalating demand for sustainable network infrastructures, we present an innovative approach integrating advanced techniques to optimise energy consumption and performance in dynamic communication networks. Addressing the challenge of achieving green network management within the realm of Future Internet and Software-Defined Networking (SDN), our proposed system leverages Federated Learning, Software-Defined WAN (SD-WAN) with Edge Intelligence, and Named Data Networking (NDN). By employing Federated Learning, our system enables collaborative model training across distributed network nodes, ensuring data privacy while facilitating localised decision-making. SD-WAN with Edge Intelligence enhance routing and traffic management at the network edge, leveraging local insights to optimise energy consumption and performance. Furthermore, Named Data Networking revolutionises content delivery by prioritising named data objects, reducing redundant traffic and enhancing content caching efficiency. The system’s flow involves real-time data collection, Federated Learning-based analysis, localised decision-making driven by SD-WAN with Edge Intelligence, and optimised content delivery through Named Data Networking. Results demonstrate substantial improvements in energy efficiency, network performance, and sustainability metrics, underscoring the effectiveness of our AI-driven approach in green network management for the evolving landscape of Future Internet and SDN environments. © 2024 Elsevier B.V., All rights reserved.