In order to meet the extremely heterogeneous requirements of the next generation wireless
communication networks, research community is increasingly dependent on using machine …

With the increasing penetration of distributed energy resources (DERs) in grid edge,
including renewable generation, flexible loads, and storage, accurate prediction of …

We investigate training machine learning (ML) models across a set of geo-distributed,
resource-constrained clusters of devices through unmanned aerial vehicles (UAV) swarms …

The Metaverse offers a second world beyond reality, where boundaries are non-existent,
and possibilities are endless through engagement and immersive experiences using the …

Despite the rapid growth of successful examples of Federated Learning (FL), it faces the
heterogeneity of data, models, and devices in emerging applications of Industrial Internet of …

The deployment of the fifth-generation (5G) wireless networks in Internet of Everything (IoE)
applications and future networks (eg, sixth-generation (6G) networks) has raised a number …

Federated learning (FL) is a promising technique for resolving the rising privacy and security
concerns. Its main ingredient is to cooperatively learn the model among the distributed …

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 …

The fast development of mobile communication and artificial intelligence (AI) technologies
greatly promotes the prosperity of the Internet of Things (IoT), where various types of IoT …