The huge amount of data generated by the Internet of Things (IoT) devices needs the
computational power and storage capacity provided by cloud, edge, and fog computing …

Sending data to the cloud for analysis was a prominent trend during the past decades,
driving cloud computing as a dominant computing paradigm. However, the dramatically …

Multi-access edge computing (MEC) has recently emerged as a novel paradigm to facilitate
access to advanced computing capabilities at the edge of the network, in close proximity to …

Technological evolution of mobile devices, such as smart phones, laptops, wearable and
other handheld devices have come up with the emergence of different user applications in …

Mobile Edge Computing (MEC) is considered an essential future service for the
implementation of 5G networks and the Internet of Things, as it is the best method of …

With the widespread adoption of various mobile applications, the amount of traffic in wireless
networks is growing at an exponential rate, which exerts a great burden on mobile core …

In recent years, fog computing has emerged as a computing paradigm to support the
computationally intensive and latency-critical applications for resource limited Internet of …

Federated learning (FL) has been proposed to efficiently and privacy-preserving distributed
machine learning architecture for the Internet of Things (IoT). In a wireless FL system, clients …

Empowered by computing resources at the network edge, data sensed from Internet of
Things (IoT) devices can be processed and stored in their nearby cloudlets to reduce the …

The edge computing (EC) paradigm brings computation and storage to the edge of the
network where data is both consumed and produced. This variation is necessary to cope …