… and networking but do not include federated DRL … of FL in the context of mobile edge networks,
whereas surveys on … to be applied in mobile edge network optimization. This motivates us …

… In this paper, we analyze how to design adaptive FL in mobile edge networks that optimally
… -cost sampling-based algorithm to learn the convergence related unknown parameters. We …

… latency but low-accuracy edge-based FL, this paper proposes a new FL framework based
on cooperative mobile edge networking called cooperative federated edge learning (CFEL) to …

… intensive resources of mobile clients in … of federated learning in mobile edge computing,
and then investigates the state-of-the-art resource optimization approaches in federated learning…

… In this article, we addressed worker selection issues to ensure reliable federated learning
in mobile networks. A reputation-based scheme was designed to select reliable and trusted …

… multiple federated learning services at the multi-access edge … resources among learning
services at each mobile device for … among mobile devices for exchanging learning information …

… Finally, we present the FL approach to solving (1) in the setting of a mobile edge network, …
policy for FL in the context of mobile edge networks. By adopting a metric termed AoU, our …

… the current deep learning techniques, we propose to integrate the Deep … Learning techniques
and Federated Learning framework with mobile edge systems, for optimizing mobile edge …

… gained attention as a solution to perform learning … applies federated learning to the demand
prediction problem, to accurately forecast the more popular application types in the network. …

… For the sake of trust, security, and efficiency of distributed AI in the mobile edge network,
this article introduces a novel blockchain-FL fusion framework. The contributions of this article …