… survey paper, we propose to answer this question: how to train distributed machine learning
models for resource-constrained IoT devices… implementation using IoT devices, and explore …

… Since the number of mobile devices and the devices in other … and federated learning can
make full use of it. The main feature of federated learning is to ensure the privacy of users, but it …

… more comprehensive review of the integration of FL in IoT networks. Particularly, we provide
a state-of-the-art survey of the applications of FL in various key IoT services such as IoT data …

… ABSTRACT This paper provides a comprehensive study of Federated Learning (FL) with an
… so it can pass through the server, or transfer the machine learning models to any device that …

… machine learning, it has still privacy concerns. In this paper, first, we present the recent
advances of federated learning towards enabling federated learning-powered IoT applications. A …

… , data collected by mobile devices is uploaded and processed centrally in a cloudbased
server or data center. In particular, data collected by IoT devices and smartphones such as …

… devices in our daily lives have shown that each IoT device can … applicable to large-scale IoT
networks and cannot exploit the … This calls for a new learning model that leaves the training …

… In this study, we thoroughly analyze the impact of heterogeneity in FL and present an
overview of the practical problems exerted by the system and statistical heterogeneity. We have …

… devices in our daily lives have shown that each IoT device can … applicable to large-scale IoT
networks and cannot exploit the … This calls for a new learning model that leaves the training …

… training upon the larger data points. In this study, various researches of federated learning
… basis of federated learning and block-chain in IoT platform. For rectifying the complication of …