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 …

With the advent of new technologies such as the Artificial Intelligence of Things (AIoT), big
data, fog computing, and edge computing, smart city applications have suffered from issues …

In vehicle ad-hoc networks, the progression of wireless communication technology to 6G,
overcomes storage, processing, privacy, and power limits to create an efficient and …

In recent years, Federated Learning (FL) has gained relevance in training collaborative
models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the …

Mobile-edge computing (MEC) has been envisioned as a promising paradigm to handle the
massive volume of data generated from ubiquitous mobile devices for enabling intelligent …

Federated learning is a privacy-preserving machine learning technique that trains models
across multiple devices holding local data samples without exchanging them. There are …

Fifth-generation (5G) cellular networks have led to the implementation of beyond 5G (B5G)
networks, which are capable of incorporating autonomous services to swarm of unmanned …

The Internet of Things (IoT) revitalizes the world with tremendous capabilities and potential
to be utilized in vehicular networks. The Smart Transport Infrastructure (STI) era depends …

In this article, we present a comprehensive study with an experimental analysis of federated
deep learning approaches for cyber security in the Internet of Things (IoT) applications …

The terrestrial networks face the challenges of severe cost inefficiency and low feasibility to
provide seamless services anytime and anywhere, especially in the extreme or hotspot …