1.3k citations · 2.7k across the 12 of their papers we have counts for
13 papers
A Joint Energy and Latency Framework for Transfer Learning over 5G Industrial Edge Networks
Bo Yang, Omobayode Fagbohungbe, Xuelin Cao +4
In this paper, we propose a transfer learning (TL)-enabled edge-CNN framework for 5G industrial edge networks with privacy-preserving characteristic. In particular, the edge server…
Deep Reinforcement Learning and Permissioned Blockchain for Content Caching in Vehicular Edge Computing and Networks
Yueyue Dai, Du Xu, Ke Zhang +2
Vehicular Edge Computing (VEC) is a promising paradigm to enable huge amount of data and multimedia content to be cached in proximity to vehicles. However, high mobility of vehicle…
Edge Intelligence for Energy-efficient Computation Offloading and Resource Allocation in 5G Beyond
Yueyue Dai, Ke Zhang, Sabita Maharjan +1
5G beyond is an end-edge-cloud orchestrated network that can exploit heterogeneous capabilities of the end devices, edge servers, and the cloud and thus has the potential to enable…
Deep Reinforcement Learning for Stochastic Computation Offloading in Digital Twin Networks
Yueyue Dai, Ke Zhang, Sabita Maharjan +1
The rapid development of Industrial Internet of Things (IIoT) requires industrial production towards digitalization to improve network efficiency. Digital Twin is a promising techn…
Low-latency Federated Learning and Blockchain for Edge Association in Digital Twin empowered 6G Networks
Yunlong Lu, Xiaohong Huang, Ke Zhang +2
Emerging technologies such as digital twins and 6th Generation mobile networks (6G) have accelerated the realization of edge intelligence in Industrial Internet of Things (IIoT). T…
Adaptive Federated Learning and Digital Twin for Industrial Internet of Things
Wen Sun, Shiyu Lei, Lu Wang +2
Industrial Internet of Things (IoT) enables distributed intelligent services varying with the dynamic and realtime industrial devices to achieve Industry 4.0 benefits. In this pape…