Energy-Efficient Green Computing Techniques for Edge Devices Using Attention-Guided Federated Learning

Green computing has emerged as an essential approach for reducing energy consumption and improving the sustainability of modern distributed systems, particularly in resource-constrained edge devices. With the rapid growth of Internet of Things (IoT) applications and edge computing environments, there is an increasing need for intelligent learning frameworks that minimize computational overhead while maintaining high model performance. This study proposes an energy-efficient green computing framework using Attention-Guided Federated Learning (AGFL) for edge devices.