[HTML][HTML] Asynchronous federated learning on heterogeneous devices: A survey

C Xu, Y Qu, Y Xiang, L Gao - Computer Science Review, 2023 - Elsevier
Federated learning (FL) is a kind of distributed machine learning framework, where the
global model is generated on the centralized aggregation server based on the parameters of …

[HTML][HTML] Digital twin—Cyber replica of physical things: Architecture, applications and future research directions

C Qian, X Liu, C Ripley, M Qian, F Liang, W Yu - Future Internet, 2022 - mdpi.com
The Internet of Things (IoT) connects massive smart devices to collect big data and carry out
the monitoring and control of numerous things in cyber-physical systems (CPS). By …

[HTML][HTML] Towards asynchronous federated learning for heterogeneous edge-powered internet of things

Z Chen, W Liao, K Hua, C Lu, W Yu - Digital Communications and Networks, 2021 - Elsevier
The advancement of the Internet of Things (IoT) brings new opportunities for collecting real-
time data and deploying machine learning models. Nonetheless, an individual IoT device …

Machine learning for security and the internet of things: the good, the bad, and the ugly

F Liang, WG Hatcher, W Liao, W Gao, W Yu - Ieee Access, 2019 - ieeexplore.ieee.org
The advancement of the Internet of Things (IoT) has allowed for unprecedented data
collection, automation, and remote sensing and actuation, transforming autonomous …

[HTML][HTML] A survey of deep reinforcement learning application in 5G and beyond network slicing and virtualization

C Ssengonzi, OP Kogeda, TO Olwal - Array, 2022 - Elsevier
Abstract The 5th Generation (5G) and beyond networks are expected to offer huge
throughputs, connect large number of devices, support low latency and large numbers of …

Recent advances in artificial intelligence for wireless internet of things and cyber–physical systems: A comprehensive survey

BA Salau, A Rawal, DB Rawat - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
Advances in artificial intelligence (AI) and wireless technology are driving forward the large
deployment of interconnected smart technologies that constitute cyber–physical systems …

Edge intelligence for data handling and predictive maintenance in IIOT

T Hafeez, L Xu, G Mcardle - IEEE Access, 2021 - ieeexplore.ieee.org
The use of IoT has become pervasive and IoT devices are common in many domains.
Industrial IoT (IIoT) utilises IoT devices and sensors to monitor machines and environments …

Zero knowledge clustering based adversarial mitigation in heterogeneous federated learning

Z Chen, P Tian, W Liao, W Yu - IEEE Transactions on Network …, 2020 - ieeexplore.ieee.org
The simultaneous development of deep learning techniques and Internet of Things
(IoT)/Cyber-physical Systems (CPS) technologies has afforded untold possibilities for …

Toward deep transfer learning in industrial internet of things

X Liu, W Yu, F Liang, D Griffith… - IEEE Internet of things …, 2021 - ieeexplore.ieee.org
Machine learning techniques have been widely adopted to assist in data analysis in a
variety of Internet of Things (IoT) systems. To enable flexible use of trained learning models …

Survey of graph neural networks and applications

F Liang, C Qian, W Yu, D Griffith… - … and Mobile Computing, 2022 - Wiley Online Library
The advance of deep learning has shown great potential in applications (speech, image,
and video classification). In these applications, deep learning models are trained by …