Future Internet, Volume 15, Issue 11
2023 November - 25 articles
Cover Story: With 6G technology on the rise, the need for a robust interconnected intelligence network has grown. Federated Learning (FL), a key distributed learning technique, shows promise. However, the integration of IoT applications and virtualization introduces diverse devices to wireless networks, varying in computation, communication, and storage resources. Our study contributes to the knowledge in this field by implementing FL processes tailored for 6G, using Raspberry PIs and virtual machines as client nodes. Our analysis delves into the impact of computational resources, data availability, and heating issues across heterogeneous devices, using knowledge transfer and pre-trained networks in our work. Our research emphasizes the crucial role of AI in 6G IoT scenarios, offering a framework for FL implementation. View this paper
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