… introduce fog computing to the federated learning framework. … 1) We propose a federated
learning scheme in fog computing… practical application scenarios for federated learning. 2) We …

… could provide incentives to federated learning participants. … The first one is federated
learning only requires the exchange … in blockchain, fog computing, and federated learning. We …

… , federated learning integrated with fog computing has … federated learning GALAXY in
vehicular fog computing, the first … of non-cloud-assisted fog computing. For enhancing the practical…

… of the heterogeneous data in federated learning. We propose an … federated learning, which
participates in the fog computing … computational costs and improve convergence in federated …

… based on the existing centralized learning strategies, especially at the edge … federated
learning-enabled intelligent F-RANs is proposed, which can take full advantage of fog computing …

… The edge/fog resources are often less powerful compared to … , Federated Learning (FL),
which is a machine learning … -suited to edge/fog computing environments, where data privacy is …

… In this work, we propose and implement a fog computingbased distributed FL framework—FogFL—for
resourceconstrained IoT environments. As shown in Fig. 1, we consider the …

… Federated Learning (PPFL) based on an efficient additive secret sharing scheme in the fog
computing scenario. We combine additive secret sharing with federated learning to protect …

… improve the resource utilization of FL-supported fog-cloud 106 networks in the literature… Fog
Learning 108 (FogL), which leverages the multi-layer network structure of 109 fog computing …

… the federated learning … federated learning architecture, empowered by fog federations,
devised for the mobile environment. In our architecture, fog computing providers form stable fog …