495 citations · 598 across the 22 of their papers we have counts for
8 papers · 1 filter
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…
Edge Intelligence Empowered UAVs for Automated Wind Farm Monitoring in Smart Grids
Hwei-Ming Chung, Sabita Maharjan, Yan Zhang +2
With the exploitation of wind power, more turbines will be deployed at remote areas possibly with harsh working conditions (e.g., offshore wind farm). The adverse working environme…
Distributed Deep Reinforcement Learning for Intelligent Load Scheduling in Residential Smart Grids
Hwei-Ming Chung, Sabita Maharjan, Yan Zhang +1
The power consumption of households has been constantly growing over the years. To cope with this growth, intelligent management of the consumption profile of the households is nec…