FedMEM: Adaptive Personalized Federated Learning Framework for Heterogeneous Mobile Edge Environments

FedMEM: Adaptive Personalized Federated Learning Framework for Heterogeneous Mobile Edge Environments

Abstract With the growth of the Internet of Things (IoT) and communication technologies, edge devices have become more diverse. This diversity has increased the computational load on these systems and led to differences between devices. In mobile edge computing, variations in communication and compu...

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Bibliographic Details
Main Authors: Chen Ximing, He Xilong, Cheng Du, Wu Tiejun, Tian Qingyu, Chen Rongrong, Qiu Jing
Format: Article
Language:English
Published: Springer 2025-04-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Mobile computing
Personalized federated learning
Wireless communication
System heterogeneity
Online Access:https://doi.org/10.1007/s44196-025-00814-7
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https://doi.org/10.1007/s44196-025-00814-7

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