Optimizing resource allocation in industrial IoT with federated machine learning and edge computing integration

The study explores resource allocation in Federated Machine Learning (FedML) for the Industrial Internet of Things (IIoT), focusing on efficient and privacy-conscious data processing. It proposes optimizing the FedML training process to enhance system performance and ensure data privacy. The researc...

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Autors principals:	Ala'a R. Al-Shamasneh, Faten Khalid Karim, Yu Wang
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2025-09-01
Col·lecció:	Results in Engineering
Matèries:	Industrial Internet of Things Federated learning Resource allocation Mobile edge computing
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S2590123025024570
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