| A WOA-Based Optimization Approach for Task Scheduling in Cloud Computing Systems X Chen, L Cheng, C Liu, Q Liu, J Liu, Y Mao, J Murphy IEEE Systems Journal 14 (3), 3117-3128, 2020 | 265 | 2020 |
| BSAS: a Blockchain-Based Trustworthy and Privacy-Preserving Speed Advisory System J Li, S Li, L Cheng, Q Liu, J Pei, S Wang IEEE Transactions on Vehicular Technology 71 (11), 11421-11430, 2022 | 99 | 2022 |
| Deep Reinforcement Learning for Communication Flow Control in Wireless Mesh Networks Q Liu, L Cheng, AL Jia, C Liu IEEE Network, 1-8, 2021 | 84 | 2021 |
| Deep Reinforcement Learning for Load-Balancing Aware Network Control in IoT Edge Systems Q Liu, T Xia, L Cheng, MV Eijk, T Ozcelebi, Y Mao IEEE Transactions on Parallel and Distributed Systems, 1-12, 2021 | 69 | 2021 |
| Safe and Secure Wireless Power Transfer Networks: Challenges and Opportunities in RF-Based Systems Q Liu, KS Yıldırım, P Pawełczak, M Warnier IEEE Communication Magazine 54 (9), 74 - 79, 2016 | 65 | 2016 |
| Network-Aware Locality Scheduling for Distributed Data Operators in Data Centers L Cheng, Y Wang, Q Liu, DHJ Epema, C Liu, Y Mao, J Murphy IEEE Transactions on Parallel and Distributed Systems, 2021 | 56 | 2021 |
| Computer Vision-Based Weight Estimation of Livestock: a Systematic Literature Review R Dohmen, C Catal, Q Liu New Zealand Journal of Agricultural Research, 1-21, 2021 | 55 | 2021 |
| Resource Management Schemes for Cloud-Native Platforms with Computing Containers of Docker and Kubernetes Y Mao, Y Fu, S Gu, S Vhaduri, L Cheng, Q Liu arXiv preprint arXiv:2010.10350, 2020 | 48 | 2020 |
| Deep Reinforcement Learning for IoT Network Dynamic Clustering in Edge Computing Q Liu, L Cheng, T Ozcelebi, J Murphy, J Lukkien 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid …, 2019 | 41 | 2019 |
| Cluster-Based Flow Control in Hybrid Software-Defined Wireless Sensor Networks Q Liu, L Cheng, R Alves, T Ozcelebi, F Kuipers, G Xu, J Lukkien, S Chen Computer Networks 187, 107788, 2021 | 38 | 2021 |
| Speculative Container Scheduling for Deep Learning Applications in a Kubernetes Cluster Y Mao, Y Fu, W Zheng, L Cheng, Q Liu, D Tao IEEE Systems Journal, 2021 | 37 | 2021 |
| Image-Based Body Mass Prediction of Heifers Using Deep Neural Networks R Dohmen, C Catal, Q Liu Biosystems Engineering 204, 283-293, 2021 | 34 | 2021 |
| The Internet of Lights: an Open Reference Architecture and Implementation for Intelligent Solid State Lighting Systems E Mathews, SS Guclu, Q Liu, T Ozcelebi, JJ Lukkien Energies 10 (8), 1187, 2017 | 25 | 2017 |
| Differentiate Quality of Experience Scheduling for Deep Learning Inferences with Docker Containers in the Cloud Y Mao, W Yan, Y Song, Y Zeng, M Chen, L Cheng, Q Liu IEEE Transactions on Cloud Computing, 2022 | 24 | 2022 |
| Green Wireless Power Transfer Networks Q Liu, M Goliński, P Pawełczak, M Warnier IEEE Journal on Selected Areas in Communications 34 (5), 1740 - 1756, 2016 | 22 | 2016 |
| Advancements in Accelerating Deep Neural Network Inference on AIoT Devices: A Survey L Cheng, Y Gu, Q Liu, L Yang, C Liu, Y Wang IEEE Transactions on Sustainable Computing, 2024 | 21 | 2024 |
| Perpetual Bluetooth communications for the IoT Q Liu, W IJntema, A Drif, P Pawełczak, M Zuniga, KS Yıldırım IEEE Sensors Journal 21 (1), 829-837, 2020 | 15 | 2020 |
| Gradient-Based Distance Estimation for Spatial Computers Q Liu, A Pruteanu, S Dulman Computer Journal 56 (12), 1469-1499, 2013 | 15 | 2013 |
| GDE: a Distributed Gradient-Based Algorithm for Distance Estimation in Large-Scale Networks Q Liu, A Pruteanu, S Dulman ACM International Conference on Modeling, Analysis and Simulation of …, 2011 | 14 | 2011 |
| MPC-CSAS: Multi-Party Computation for Real-Time Privacy-Preserving Speed Advisory Systems M Liu, L Cheng, Y Gu, Y Wang, Q Liu, NE O'Connor IEEE Transactions on Intelligent Transportation Systems, 2021 | 13 | 2021 |
Long ChengProfessor, North China Electric Power Universityncepu.edu.cn의 이메일 확인됨