Two-Layer Federated Learning With Heterogeneous Model Aggregation for 6G Supported Internet of Vehicles

The vision of the upcoming 6G technologies that have fast data rate, low latency, and ultra-dense network, draws great attentions to the Internet of Vehicles (IoV) and Vehicle-to-Everything (V2X) communication for intelligent transportation systems. There is an urgent need for distributed machine le...

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Veröffentlicht in:	IEEE transactions on vehicular technology Jg. 70; H. 6; S. 5308 - 5317
Hauptverfasser:	Zhou, Xiaokang, Liang, Wei, She, Jinhua, Yan, Zheng, Wang, Kevin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.06.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	6G mobile communication 6G technology Agglomeration Cloud computing Collaborative work Computational modeling Computer architecture Data models Distributed databases End-edge-cloud computing Federated learning Heterogeneous data Intelligent transportation systems Internet of Vehicles Learning Machine learning Multilayers Network latency Object detection Object recognition Roadsides Systems analysis Training Transportation networks Vehicles
ISSN:	0018-9545, 1939-9359
Online-Zugang:	Volltext
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