Adaptive federated learning for resource-constrained IoT devices through edge intelligence and multi-edge clustering

Adaptive federated learning for resource-constrained IoT devices through edge intelligence and multi-edge clustering

Abstract In the rapidly growing Internet of Things (IoT) landscape, federated learning (FL) plays a crucial role in enhancing the performance of heterogeneous edge computing environments due to its scalability, robustness, and low energy consumption. However, one of the major challenges in such envi...

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Bibliographic Details
Main Authors: Fahad Razaque Mughal, Jingsha He, Bhagwan Das, Fayaz Ali Dharejo, Nafei Zhu, Surbhi Bhatia Khan, Saeed Alzahrani
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
Subjects:
Internet of things
Resource management
Edge artificial intelligence
Heterogeneous cluster networks
Edge computing
Federated learning
Online Access:https://doi.org/10.1038/s41598-024-78239-z
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https://doi.org/10.1038/s41598-024-78239-z

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