Federated learning is an emerging machine learning paradigm where clients train models
locally and formulate a global model based on the local model updates. To identify the state …

In recent years, the enhanced sensing and computation capabilities of Internet-of-Things
(IoT) devices have opened the doors to several mobile crowdsensing applications. In mobile …

Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory
Approach Page 1 1 Incentive Design for Efficient Federated Learning in Mobile Networks: A …

Industrial Internet of Things (IIoT) lays a new paradigm for the concept of Industry 4.0 and
paves an insight for new industrial era. Nowadays smart machines and smart factories use …

Abstract 5 G is the fifth generation of cellular networks. It enables billions of connected
devices to gather and share information in real time; a key facilitator in Industrial Internet of …

Federated learning (FL) is a new technology that has been a hot research topic. It enables
the training of an algorithm across multiple decentralized edge devices or servers holding …

Federated Learning (FL) is known to perform Machine Learning tasks in a distributed
manner. Over the years, this has become an emerging technology especially with various …

Machine learning (ML), and deep learning (DL) in particular, play a vital role in providing
smart services to the industry. These techniques, however, suffer from privacy and security …

Federated learning is a distributed machine learning approach that enables a large number
of edge/end devices to perform on-device training for a single machine learning model …

Federated learning (FL) has been increasingly considered to preserve data training privacy
from eavesdropping attacks in mobile-edge computing-based Internet of Things (EdgeIoT) …