A Framework Integrating Federated Learning and Fog Computing Based on Client Sampling and Dynamic Thresholding Techniques

The exponential growth in the number of Internet of Things (IoT) devices and the vast quantity of data they generate present a significant challenge to the efficacy of traditional centralized training models. Federated Learning (FL) is a machine learning framework that effectively addresses this iss...

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Hlavní autoři:	Dang van Thang, Artem Volkov, Ammar Muthanna, Ibrahim A. Elgendy, Reem Alkanhel, Dushantha Nalin K. Jayakody, Andrey Koucheryavy
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2025-01-01
Edice:	IEEE Access
Témata:	Federated learning fog computing client sampling dynamic thresholding
On-line přístup:	https://ieeexplore.ieee.org/document/11007538/
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