… era of edge computing and learning-assisted applications. In this paper, we investigate the
Hierarchical Federated Learning (… that affect the learning performance (ie, learning speed and …

… However, in a large-scale and complex mobile edge network, heterogeneous devices with
… -edge solutions. Furthermore, we present the applications of FL for mobile edge network …

… private data, a new machine learning model has emerged, namely federated learning (FL),
that … learning taking place in a data center, FL usually operates in a wireless edge network …

… communication resources at the edge of vehicular networks. Federated learning in VEC
is … Miao, “Federated learning in mobile edge networks: A comprehensive survey,” 2019. [Online…

… from the previous work on federated learning. McMahan et al… , the accuracy of convolutional
neural networks trained with F … To address this statistical challenge of federated learning, we …

… The federated learning technique (FL) supports the collaborative training of machine
learning and deep learning models for edge network … of federated learning in edge networks. …

… 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 …

… In this article, we first illustrate the process of FL-based localization at the edge network, and
… In the next section, the framework of FL-based localization at the mobile edge network is …

… Nevertheless, since wireless edge networks are mainly based on the cellular structure, such
a fully decentralized setting may not fit in well with the current network architecture. Another …

Federated Learning (FL) is a promising privacy-preserving distributed machine learning
paradigm. However, communication inefficiency remains the key bottleneck that impedes its …