… decision of device selection and computing and spectrum resource allocation for optimizing
federated learning (FL) performance in distributed industrial Internet of Things (IIoT) networks…

… 3) We integrate differential privacy into federated learning to further protect data privacy. We
… In Section III, we describe permissioned blockchain and federated learning for data sharing …

… learning is not directly applicable to IIoT devices. We investigate federated learning to
train … The integration of fog/edge with federated learning maximizes the value of distributed …

… ment of industrial informatization have promoted the proliferation of the Industrial Internet
of Things (IIoT), with its capability to increase productivity and efficiency in industries [1]. It is …

… smart factories use machine learning/deep learning based models for … In order to address
this issue, Federated Learning (FL) … in multi-industrial IoT. This work proposed a novel deep …

… Industrial IoT, where DTs capture the characteristics of industrial devices to assist federated
learning… -based aggregation is proposed in federated learning to alleviate the effects of such …

… federated learning approach for device failure detection in IIoT. First, we present a platform
architecture of blockchain-based federated learning … distance weighted federated averaging (…

… models trained at the edge hinder the success of Federated Learning (FL), we have proposed
in … predictive maintenance models as a proxy for industrial IoT (IIoT) services. The results …

… industrial data, federated learning (FL) was introduced to collaboratively train shared machine
learn… skew in class distribution and degrade industrial FL performance. This challenge has …

… in industrial Internet of Things (IoT). However, for privacy issues, traditional data-gathering
centralized learning is not applicable to industrial … Recently, federated learning has received …