Edge computing with artificial intelligence: A machine learning perspective
Recent years have witnessed the widespread popularity of Internet of things (IoT). By
providing sufficient data for model training and inference, IoT has promoted the development …
providing sufficient data for model training and inference, IoT has promoted the development …
Enabling massive IoT toward 6G: A comprehensive survey
Nowadays, many disruptive Internet-of-Things (IoT) applications emerge, such as
augmented/virtual reality online games, autonomous driving, and smart everything, which …
augmented/virtual reality online games, autonomous driving, and smart everything, which …
Edge learning for B5G networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing
To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …
increasingly appealing to exploit distributed data communication and learning. Specifically …
Federated learning in smart cities: Privacy and security survey
Over the last decade, smart cities (SC) have been developed worldwide. Implementing big
data and the internet of things improves the monitoring and integration of different …
data and the internet of things improves the monitoring and integration of different …
Federated deep learning for cyber security in the internet of things: Concepts, applications, and experimental analysis
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 …
deep learning approaches for cyber security in the Internet of Things (IoT) applications …
Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: Challenges, recent advances, and future directions
Full leverage of the huge volume of data generated on a large number of user devices for
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
Federated reinforcement learning: Techniques, applications, and open challenges
This paper presents a comprehensive survey of Federated Reinforcement Learning (FRL),
an emerging and promising field in Reinforcement Learning (RL). Starting with a tutorial of …
an emerging and promising field in Reinforcement Learning (RL). Starting with a tutorial of …
Secure and provenance enhanced internet of health things framework: A blockchain managed federated learning approach
Recent advancements in the Internet of Health Things (IoHT) have ushered in the wide
adoption of IoT devices in our daily health management. For IoHT data to be acceptable by …
adoption of IoT devices in our daily health management. For IoHT data to be acceptable by …
Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions
Many enterprise companies migrate their services and applications to the cloud to benefit
from cloud computing advantages. Meanwhile, the rapidly increasing number of connected …
from cloud computing advantages. Meanwhile, the rapidly increasing number of connected …
Machine learning for large-scale optimization in 6g wireless networks
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …