1 citations · 1 across the 4 of their papers we have counts for
5 papers
Oh-Trust: Overbooking and Hybrid Trading-empowered Resource Scheduling with Smart Reputation Update over Dynamic Edge Networks
Houyi Qi, Minghui Liwang, Liqun Fu +3
Incentive-driven computing resource sharing is crucial for meeting the ever-growing demands of emerging mobile applications. Although conventional spot trading offers a solution, i…
PAST: Pilot and Adaptive Orchestration for Timely and Resilient Service Delivery in Edge-Assisted UAV Networks under Spatio-Temporal Dynamics
Houyi Qi, Minghui Liwang, Liqun Fu +4
Incentive-driven resource trading is essential for uncrewed aerial vehicle (UAV) applications with intensive, time-sensitive computing demands. Traditional spot trading suffers fro…
Towards Seamless Hierarchical Federated Learning under Intermittent Client Participation: A Stagewise Decision-Making Methodology
Minghong Wu, Minghui Liwang, Yuhan Su +5
Federated Learning (FL) offers a pioneering distributed learning paradigm that enables devices/clients to build a shared global model. This global model is obtained through frequen…
HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning
Xiaohong Yang, Minghui Liwang, Xianbin Wang +4
The rapid growth of AI-enabled Internet of Vehicles (IoV) calls for efficient Machine Learning (ML) solutions that can handle high vehicular mobility and decentralized data. This h…
Accelerating the Delivery of Data Services over Uncertain Mobile Crowdsensing Networks
Minghui Liwang, Zhipeng Cheng, Wei Gong +6
The challenge of exchanging and processing of big data over mobile crowdsensing (MCS) networks calls for designing seamless data service provisioning mechanisms to enable utilizati…