■ Journal:

  • BSAS: A Blockchain-Based Trustworthy and Privacy-Preserving Speed Advisory System. Jianbin Li, Shike Li, Long Cheng, Qingzhi Liu, Jiaming Pei, Shen Wang. IEEE Transactions on Vehicular Technology. 2022.
  • Differentiate Quality of Experience Scheduling for Deep Learning Inferences with Docker Containers in the Cloud. Ying Mao, Weifeng Yan, Yun Song, Yue Zeng, Ming Chen, Long Cheng, Qingzhi Liu. IEEE Transactions on Cloud Computing. 2022.
  • Speculative Container Scheduling for Deep Learning Applications in a Kubernetes Cluster. Ying Mao, Yuqi Fu, Wenjia Zheng, Long Cheng, Qingzhi Liu, Dingwen Tao. IEEE Systems Journal. 2021. 
  • Qingzhi Liu, Tiancong Xia, Long Cheng, Merijn Van Eijk, Tanir Ozcelebi, Ying Mao. Deep Reinforcement Learning for Load-Balancing Aware Network Control in IoT Edge Systems. IEEE Transactions on Parallel and Distributed Systems. 2021.
  • Roel Dohmen, Cagatay Catal, Qingzhi Liu. Image-Based Body Mass Prediction of Heifers Using Deep Neural Networks. Biosystems Engineering. 2021.
  • Qingzhi Liu, Long Cheng, Adele Lu Jia, Cong Liu. Deep Reinforcement Learning for Communication Flow Control in Wireless Mesh Networks. IEEE Network. 2021. (Impact Factor: 8.8)
  • Mingming Liu, Long Cheng, Yingqi Gu, Ying Wang, Qingzhi Liu, Noel E O’Connor. MPC-CSAS: Multi-Party Computation for Real-Time Privacy-Preserving Speed Advisory Systems. IEEE Transactions on Intelligent Transportation Systems. 2021. (Impact Factor: 6.3)
  • Roel Dohmen, Cagatay Catal, Qingzhi Liu. Computer Vision-Based Weight Estimation of Livestock: a Systematic Literature Review. Journal of Agricultural Research. 2021.
  • Long Cheng, Ying Wang, Qingzhi Liu, Dick HJ Epema, Cheng Liu, Ying Mao, John Murphy. Network-Aware Locality Scheduling for Distributed Data Operators in Data Centers. IEEE Transactions on Parallel and Distributed Systems. 2021.
  • Qingzhi Liu, Long Cheng, Renan Alves, Tanir Ozcelebi, Fernando Kuipers, Guixian Xu, Johan Lukkien, Shanzhi Chen. Cluster-Based Flow Control in Hybrid Software-Defined Wireless Sensor Networks. Computer Networks. 2021.
  • Qingzhi Liu, Wieger IJntema, Anass Drif, Przemysław Pawełczak, Marco Zuniga, Kasım Sinan Yıldırım. Perpetual Bluetooth Communications for the IoT. IEEE Sensors Journal. 2020.
  • Xuan Chen, Long Cheng, Cong Liu, Qingzhi Liu, Jinwei Liu, Ying Mao, John Murphy. A WOA-Based Optimization Approach for Task Scheduling in Cloud Computing Systems. IEEE Systems Journal. 2020.
  • Long Cheng, Spyros Kotoulas, Qingzhi Liu, Ying Wang. Load-balancing Distributed Outer Joins through Operator Decomposition. Journal of Parallel and Distributed Computing. Vol. 132, 2019.
  • Emi Mathews, Salih Serdar Guclu, Qingzhi Liu, Tanir Ozcelebi, Johan J Lukkien. The Internet of Lights: An Open Reference Architecture and Implementation for Intelligent Solid State Lighting Systems. Energies, Volume. 10, Issue 8, 2017.
  • Qingzhi Liu, Michał Golinński, Przemysław Pawełczak, Martijn Warnier. Green wireless power transfer networks. IEEE Journal on Selected Areas in Communications, Volume 34, Issue 5, 2016. (Impact Factor: 8.085)
  • Qingzhi Liu, Kasım Sinan Yıldırım, Przemysław Pawełczak, Martijn Warnier. Safe and Secure Wireless Power Transfer Networks: Challenges and Opportunities in RF-Based Systems. IEEE Communication Magazine, Volume 54, Issue 9, 2016. (Impact Factor: 10.435)
  • Qingzhi Liu, Andrei Pruteanu, Stefan Dulman. Gradient-Based Distance Estimation for Spatial Computers. Computer Journal, Volume 56, Issue 12, 2013.

■ Conference:

  • Performance Evaluation of Resource Management Schemes for Cloud Native Platforms with Computing Containers. Yuqi Fu, Naseem Machlovi, Ying Mao, Jiayin Wang, Long Cheng, Qingzhi Liu. IEEE International Performance, Computing, and Communications Conference (IPCCC). 2022.
  • Long Cheng, Cong Liu, Qingzhi Liu, Yucong Duan, and John Murphy. Learning Process Models in IoT Edge. Proc. IEEE World Congress on Services (SERVICES), pp. 146-149, Milan, Italy, July 2019.
  • Tianyu Bi, Qingzhi Liu, Tanir Ozcelebi, Dragan Sekulovski. PCANN: Distributed ANN Architecture for Image Recognition in Resource-Constrained IoT Devices. Proc. IEEE Intelligent Environment Conference (IE), 2019.
  • Qingzhi Liu, Long Cheng, Tanir Ozcelebi, Johan Lukkien. Deep Reinforcement Learning for IoT Network Dynamic Clustering in Edge Computing. Proc. IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 600-603, Larnaca, Cyprus, May 2019.
  • Srikanth Sistu, Qingzhi Liu, Tanir Ozcelebi, Esko Dijk, Teresa Zotti. Performance Evaluation of Thread Protocol based Wireless Mesh Networks for Lighting Systems. International Symposium on Networks, Computers and Communications (ISNCC), 2019.  (Best Paper)
  • Qingzhi Liu, Tanir Ozcelebi, Long Cheng, Fernando Kuipers, Johan Lukkien. CluFlow: Cluster-based Flow Management in Software-Defined Wireless Sensor Networks. Proc. IEEE Wireless Communications and Networking Conference (WCNC), 2019.
  • Long Cheng, John Murphy, Qingzhi Liu, Chunliang Hao, Georgios Theodoropoulos. Minimizing Network Traffic for Distributed Joins Using Lightweight Locality-Aware Scheduling. Proc. European Conference on Parallel Processing (EuroPar), 2018.
  • Ivar in’t Veen, Qingzhi Liu, Przemyslaw Pawelczak, Aaron Parks, Joshua R Smith. BLISP: Enhancing backscatter radio with active radio for computational RFIDs. Proc. IEEE International Conference on RFID (RFID), 2016.
  • Thomas C King, Qingzhi Liu, Gleb Polevoy, Mathijs de Weerdt, Virginia Dignum, M Birna van Riemsdijk, Martijn Warnier. Request Driven Social Sensing. Proc. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2014.
  • Venkatraman Iyer, Qingzhi Liu, Stefan Dulman, Koen Langendoen. Adaptive Online Estimation of Temporal Connectivity in Dynamic Wireless Networks. Proc. IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO), 2013.
  • Qingzhi Liu, Stefan Dulman, Martijn Warnier. AREA: an Automatic Runtime Evolutionary Adaptation mechanism for Creating Self-Adaptation Algorithms in Wireless Networks. Proc. Spatial Computing Workshop in the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2013.
  • Qingzhi Liu, Andrei Pruteanu, Stefan Dulman. GDE: a Distributed Gradient-Based Algorithm for Distance Estimation in Large-Scale Networks. Proc. ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), 2011.

■ Google Scholar