Enhancing Edge Computing Performance for IoT Applications Using Federated Learning Techniques

Lucas Henry Young
Grace Olivia Hall

International Journal of Computer Technology and Science
Vol. 1 No. 1 (2024): January : International Journal of Computer Technology and Science

As Internet of Things (IoT) devices proliferate, edge computing has become essential for reducing latency and improving data privacy. This paper explores federated learning as a method to enhance the efficiency and security of edge computing systems. We implement and evaluate federated models in various IoT environments, demonstrating how federated learning can reduce data transfer and computation load while maintaining accuracy in data analysis.