To build intelligent model learning in conventional architecture, the local data are required to
be transmitted toward the cloud server, which causes heavy backhaul congestion, leakage …

New technological advancements in wireless networks have enlarged the number of
connected devices. The unprecedented surge of data volume in wireless systems …

The ultimate goal of Internet of Things (IoT) technology is to evolve into the Internet of
Everything. Two key elements of IoT are artificial intelligence (AI) for smart devices and the …

To leverage massive distributed data and computation resources, machine learning in the
network edge is considered to be a promising technique, especially for large-scale model …

The high-speed mobile networks offer great potentials to many future intelligent applications,
such as autonomous vehicles in smart transportation systems. Such networks provide the …

The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …

Federated learning (FL) has been considered as a promising learning framework for future
machine learning systems due to its privacy preservation and communication efficiency. In …

The analysis of data coming from massively deployed Internet of Things (IoT) devices pave
the way to a myriad of intelligent applications in several vertical domains. Federated …

To reap the benefit of big data generated by the massive number of Internet of Things (IoT)
devices while preserving data privacy, federated learning (FL) has been proposed to enable …

The explosive growth of smart devices (eg, mobile phones, vehicles, drones) with sensing,
communication, and computation capabilities gives rise to an unprecedented amount of …