1.5k citations · 3.2k across the 30 of their papers we have counts for
30 papers
Cooperative Task Offloading and Block Mining in Blockchain-based Edge Computing with Multi-agent Deep Reinforcement Learning
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana +3
The convergence of mobile edge computing (MEC) and blockchain is transforming the current computing services in mobile networks, by offering task offloading solutions with security…
6G Internet of Things: A Comprehensive Survey
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana +5
The sixth generation (6G) wireless communication networks are envisioned to revolutionize customer services and applications via the Internet of Things (IoT) towards a future of fu…
Federated Learning Over Wireless Channels: Dynamic Resource Allocation and Task Scheduling
Shunfeng Chu, Jun Li, Jianxin Wang +5
With the development of federated learning (FL), mobile devices (MDs) are able to train their local models with private data and sends them to a central server for aggregation, the…
Low-Latency Federated Learning over Wireless Channels with Differential Privacy
Kang Wei, Jun Li, Chuan Ma +5
In federated learning (FL), model training is distributed over clients and local models are aggregated by a central server. The performance of uploaded models in such situations ca…
Federated Learning for Industrial Internet of Things in Future Industries
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana +4
The Industrial Internet of Things (IIoT) offers promising opportunities to transform the operation of industrial systems and becomes a key enabler for future industries. Recently,…
Federated Learning with Unreliable Clients: Performance Analysis and Mechanism Design
Chuan Ma, Jun Li, Ming Ding +3
Owing to the low communication costs and privacy-promoting capabilities, Federated Learning (FL) has become a promising tool for training effective machine learning models among di…