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Topology-Driven Synchronization Interval Optimization for Latency-Constrained Geo-Decentralized Federated Learning

Geo-decentralized federated learning (FL) can empower fully distributed model training for future large-scale 6G networks. Without the centralized parameter server, the peer-to-peer model synchronization in geo-decentralized FL would incur excessive communication overhead. Some existing studies opti...

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Tallennettuna:
Päätekijät: Qi Chen, Wei Yu, Xinchen Lyu, Zimeng Jia, Guoshun Nan, Qimei Cui
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: IEEE 2024-01-01
Sarja:IEEE Open Journal of the Communications Society
Aiheet:
Federated learning
edge intelligence
latency-constrained
communication efficiency
Linkit:https://ieeexplore.ieee.org/document/10505935/
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