124 citations · 297 across the 10 of their papers we have counts for
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3 papers · 1 filter
cs.DC2022
Asynchronous Federated Learning Based Mobility-aware Caching in Vehicular Edge Computing
Wenhua Wang, Yu Zhao, Qiong Wu +3
Vehicular edge computing (VEC) is a promising technology to support real-time applications through caching the contents in the roadside units (RSUs), thus vehicles can fetch the co…
cs.LG2022★ 1 cited
Asynchronous Federated Learning for Edge-assisted Vehicular Networks
Siyuan Wang, Qiong Wu, Qiang Fan +2
Vehicular networks enable vehicles support real-time vehicular applications through training data. Due to the limited computing capability, vehicles usually transmit data to a road…
cs.NI2022★ 1 cited
High stable and accurate vehicle selection scheme based on federated edge learning in vehicular networks
Qiong Wu, Xiaobo Wang, Qiang Fan +3
Federated edge learning (FEEL) technology for vehicular networks is considered as a promising technology to reduce the computation workload while keeping the privacy of users. In t…