AoU-Based Local Update and User Scheduling for Semi-Asynchronous Online Federated Learning in Wireless Networks

With the advent of the 5G and 6G eras and the explosive growth of mobile users, machine learning (ML) is increasingly used for extracting important information from a large amount of generated data and making intelligent decisions for complex environments. Especially, distributed ML techniques are g...

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Vydané v:	IEEE internet of things journal Ročník 11; číslo 18; s. 29673 - 29688
Hlavní autori:	Zheng, Jianing, Liu, Xiaolan, Ling, Zhuang, Hu, Fengye
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 15.09.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Age of Update (AoU) Aggregates Algorithms asynchronous federated learning (AsynFL) Clustering Computational modeling Convergence Data models Datasets Federated learning federated learning (FL) Heterogeneity Machine learning Priority scheduling priority-based user scheduling Training User satisfaction Wireless networks
ISSN:	2327-4662, 2327-4662
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