Today's advancements in wireless communication technologies have resulted in a
tremendous volume of data being generated. Most of our information is part of a widespread …

As the Internet of Things (IoT) technology advances, billions of multidisciplinary smart
devices act in concert, rarely requiring human intervention, posing significant challenges in …

One of the key foundations of 5th Generation (5G) and beyond 5G (B5G) networks is
network slicing, in which the network is partitioned into several separated logical networks …

Edge devices can offload deep neural network (DNN) inference to the cloud to overcome
energy or processing constraints. Nevertheless, offloading adds communication delay …

Federated Learning (FL) relies on on-device training to avoid the migration of devices' data
to a centralized server to address privacy leakage. Moreover, FL is feasible for scenarios …

The intelligent diagnosis of faults in industrial assets helps avoid unexpected interruptions of
critical services. Thus, machine learning systems for monitoring machinery have a …

Through multiplexing separate virtual networks on the same network infrastructure, network
slicing will lead to customization, scalability, flexibility, and isolation of services in different …

In computer vision applications, mobile devices can transfer the inference of Convolutional
Neural Networks (CNNs) to the cloud due to their computational restrictions. Nevertheless …

Massive amounts of real-time streaming network data are generated quickly because of the
exponential growth of applications. Analyzing patterns in generated flow traffic streaming …

Abstract IoT (Internet of Things) devices are fundamental to sectors such as smart homes
and cities, industry 4.0, and smart grids. Despite the benefits brought by IoT, the existence of …