… 2.1 Federated Learning FL solves the training tasks with a loose federation of participating
devices (eg, laptops, … His research interests include edge computing and federated learning. …

… edge computing applications, such as mobile application recommendation [14], federated
learning … solution to analyze and process the huge amount of data stored in edge nodes [27]. …

… The heterogeneity and autonomy of edge nodes will also reduce the efficiency of …
asynchronous federated learning method to solve this problem. This method allows edge nodes to …

… asynchronous federation learning for edge network computing can effectively assist edge-…
Although the existing blockchain-based federated learning framework can provide incentives …

… for the federated learning in edge computing especially for the … of federal learning in edge
computing much more secure. … a federated learning training model under the edge network, …

… to design a synchronous federated learning framework in which the server performs aggregation
operations when it receives local updates from all selected edge clients in each round. …

… node uses local data to train a model and then uses the model to learn the features of users
… security of edge nodes’ data, we use federated learning (FL) to enable multiple edge nodes …

… This article discusses a novel paradigm for integrating blockchain and federated learning
technology. We examined related works focusing on network structure design, performance …

… Among others, Federated Learning (FL) has been highlighted as one of the most promising
… To this end, we first propose an FL-inspired distributed learning framework for computation …

… In this paper, we propose an edge computing-based joint client selection and networking …
vehicles as edge vehicles by employing a distributed approach, and uses the edge vehicles as …