B Luo, X Li, S Wang, J Huang… - IEEE Journal on …, 2021 - ieeexplore.ieee.org
… In this paper, we analyze how to design adaptive FL in mobileedgenetworks that optimally … -cost sampling-based algorithm to learn the convergence related unknown parameters. We …
Z Zhang, Z Gao, Y Guo, Y Gong - IEEE Transactions on Mobile …, 2022 - ieeexplore.ieee.org
… latency but low-accuracy edge-based FL, this paper proposes a new FL framework based on cooperative mobileedgenetworking called cooperative federatededgelearning (CFEL) to …
… multiple federatedlearning services at the multi-access edge … resources among learning services at each mobile device for … among mobile devices for exchanging learning information …
R Yu, P Li - IEEE Network, 2021 - ieeexplore.ieee.org
… intensive resources of mobile clients in … of federatedlearning in mobileedge computing, and then investigates the state-of-the-art resource optimization approaches in federatedlearning…
… In this article, we addressed worker selection issues to ensure reliable federatedlearning in mobilenetworks. A reputation-based scheme was designed to select reliable and trusted …
… Abstract—Most conventional FederatedLearning (FL) models are using a star network … This article proposes a novel edgenetwork architecture that enables decentralizing the model …
… Finally, we present the FL approach to solving (1) in the setting of a mobileedgenetwork, … policy for FL in the context of mobileedgenetworks. By adopting a metric termed AoU, our …
… the current deep learning techniques, we propose to integrate the Deep … Learning techniques and FederatedLearning framework with mobileedge systems, for optimizing mobileedge …
R Fantacci, B Picano - CAAI Transactions on Intelligence …, 2020 - Wiley Online Library
… gained attention as a solution to perform learning … applies federatedlearning to the demand prediction problem, to accurately forecast the more popular application types in the network. …