… , a reliable global model can be quickly obtained and be shared … To ensure the reliability of
FL model parameters exchange, … future smart IoT should have large-scale distributed training …

… Moreover, an asynchronous FL scheme for resource sharing … the training process over the
large-scale healthcare system. … smart contracts [71], can provide reliable authentication for …

… the purpose of collaborative learning from a large amount of … of the learning model and an
accurate aggregation of local … federated learning scheme for resource sharing in vehicular …

… researchers nowadays to provide safe, accurate, robust and unbiased … and huge data.
Comprehensive background on data and … more on developing resource sharing techniques [153], …

… data storage, big data analytics, and big data privacy preservation. Subsequently, we … FL
for big data applications, such as smart city, smart healthcare, smart transportation, smart grid, …

… In 5G and Beyond networks, the resource sharing and incentive mechanism design for end-…
more data1 during its local training will receive a larger share of the reward pool. Moreover, …

… good approximation of the true state due to the powerful learning capability of deep learning
… equipped with huge computation and storage resources, an individual SCceNB with limited …

… to training sets, such as face recognition and medical systems. Recently, federated learning
… since it trains a model by only sharing gradients without accessing training sets. But existing …

… communication-efficient federated learning scheme in smart grids with a large number of
users … based reliable federated learning and the local model evaluation model under DP-based …

… this issue, Federated Learning (FL) technology is implemented in IIoT by the researchers
nowadays to provide safe, accurate, … and huge data. Comprehensive background on data and …