… 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 …

… Abstract—Most conventional Federated Learning (FL) models are using a star network …
This article proposes a novel edge network architecture that enables decentralizing the model …

… aspects for enabling federated learning at the network edge. We model … federated learning
via a Stackelberg game to motivate the participation of the devices in the federated learning …

… a novel edge computing assisted federated learning framework … network. The major
contributions are summarized as follows: • We introduce an edge computing assisted federated learn…