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Leijie Wu, Song Guo, Zicong Hong, Yi Liu, Wenchao Xu, and Yufeng Zhan, "Long-term Adaptive VCG Auction Mechanism for Sustainable Federated Learning with Periodical Client Shifting," IEEE Transactions on Mobile Computing, 2023.
Runze Gao, Yuanqing Xia*, Guan Wang, Liwen Yang, and Yufeng Zhan*, "Fast Subspace Identification Method Based on Containerised Cloud Workflow Processing System," IEEE Transactions on Automation Science and Engineering, 2023.
Runze Gao, Qiwen Li, Li Dai, Yufeng Zhan*, and Yuanqing Xia*, "Workflow-Based Fast Data-Driven Predictive Control With Disturbance Observer in Cloud-Edge Collaborative Architecture," IEEE Transactions on Automation Science and Engineering, 2023.
Liwen Yang, Yuanqing Xia, Lingjuan Ye, Runze Gao, and Yufeng Zhan, "A Fully Hybrid Algorithm for Deadline Constrained Workflow Scheduling in Clouds," IEEE Transactions on Cloud Computing, 2023.
Tianyu Qi, Yufeng Zhan*, Peng Li*, Jingcai Guo, and Yuanqing Xia, "Hwamei: A Learning-based Aggregation Framework for Hierarchical Federated Learning System," in Proc. of IEEE ICDCS, 2023.
Yuan Zhang, Yuanqing Xia, and Yufeng Zhan, "Total Unimodularity and Strongly Polynomial Solvability of Constrained Minimum Input Selections for Structural Controllability: An LP-based Method," IEEE Transactions on Automatic Control, 2023.
Yuan Zhang, Yuanqing Xia, and Yufeng Zhan, "On Real Structured Controllability/Stabilizability/Stability Radius: Complexity and Unified Rank-relaxation based Methods," System & Control Letters, 2023.
Haozhao Wang, Yichen Li, Wenchao Xu, Ruixuan Li, Yufeng Zhan, and Zhigang Zeng, "DaFKD: Domain-aware Federated Knowledge Distillation," in Proc. of CVPR, 2023.
Liwen Yang, Yuanqing Xia*, Xiaopu Zhang, Lingjuan Ye, and Yufeng Zhan*, "Classification-Based Diverse Workflows Scheduling in Clouds," IEEE Transactions on Automation Science and Engineering, 2022.
Liwen Yang, Lingjuan Ye, Yuanqing Xia*, and Yufeng Zhan*, "Look-ahead Workflow Scheduling with Width Changing Trend in Clouds," Future Generation Computer Systems, 2022.
Lingjuan Ye, Yuanqing Xia*, Liwen Yang, and Yufeng Zhan*, "Dynamic Scheduling Stochastic Multi-workflows with Deadline Constraints in Clouds," IEEE Transactions on Automation Science and Engineering, 2022(Accepted).
Tijin Yan, Tong Zhou, Yufeng Zhan, and Yuanqing Xia, "TFDPM: Attack Detection for Cyber-Physical Systems with Diffusion Probabilistic Models," Knowledge-Based Systems, 2022(Accepted).
Minfeng Wei, Yuanqing Xia, Yuan Zhang, Yufeng Zhan, and Bing Cui, "Distributed Consensus Control for Networked Euler–Lagrange Systems Over Directed Graphs: A Dynamic Event-triggered Approach," International Journal of Robust and Nonlinear Control, 2022(Accepted).
Lingjuan Ye, Yuanqing Xia, Siyuan Tao, Ce Yan, Runze Gao, and Yufeng Zhan, "Reliability-Aware and Energy-Efficient Workflow Scheduling in IaaS Clouds," IEEE Transactions on Automation Science and Engineering, 2022(Accepted).
Zicong Hong, Song Guo, Rui Zhang, Peng Li, Yufeng Zhan, and Wuhui Chen, "CYCLE: Sustainable Off-Chain Payment Channel Network with Asynchronous Rebalancing," in Proc. of IEEE/IFIP DSN, 2022.
Leijie Wu, Song Guo, Yi Liu, Zicong Hong, Yufeng Zhan, and Wenchao Xu, "Sustainable Federated Learning with Long-term Online VCG Auction Mechanism," in Proc. of IEEE ICDCS, 2022.
Yuan Zhang, Yuanqing Xia, and Yufeng Zhan, "A Linear Programming Approach to the Minimum Cost Sparsest Input Selection for Structured Systems," in Proc. of IEEE ACC, 2022.
Dongdong Yu, Yuanqing Xia, Di-Hua Zhai, and Yufeng Zhan, "On Distributed Fusion Estimation with Stochastic Scheduling Over Sensor Networks," Automatica, 2022.
Yi Liu, Leijie Wu, Yufeng Zhan*, Song Guo*, and Zicong Hong, "Incentive-Driven Long-term Optimization for Edge Learning by Hierarchical Reinforcement Learning," in Proc. of IEEE ICDCS, 2021.
Jie Zhang, Song Guo, Zhihao Qu, Deze Zeng, Yufeng Zhan, Qifeng Liu, and Rajendra A Akerkar, "Adaptive Federated Learning on Non-IID Data with Resource Constraint," IEEE Transactions on Computers, 2021.
Jie Zhang, Zhihao Qu, Chenxi Chen, Haozhao Wang, Yufeng Zhan, Baoliu Ye, and Song Guo, "Edge Learning: the Enabling Technology for Distributed Big Data Analytics in the Edge," ACM Computing Surveys, 2021.
Yufeng Zhan, Peng Li, Leijie Wu, and Song Guo, "L4L: Experience-Driven Computational Resource Control in Federated Learning," IEEE Transactions on Computers, 2021.
Yufeng Zhan, Peng Li, Song Guo, and Zhihao Qu, "Incentive Mechanism Design for Federated Learning: Challenges and Opportunities," IEEE Network, 2021.
Yufeng Zhan, Jie Zhang, Zicong Hong, Leijie Wu, Peng Li, and Song Guo, "A Survey of Incentive Mechanism Design for Federated Learning," IEEE Transactions on Emerging Topics in Computing, 2021. (ESI Highly Cited Paper)
Yufeng Zhan, Song Guo, Peng Li, and Jiang Zhang, "A Deep Reinforcement Learning Based Offloading Game in Edge Computing," IEEE Transactions on Computers, 2020. (Best Paper Award)
Yufeng Zhan, Chi Harold Liu, Yinuo Zhao, Jiang Zhang, and Jian Tang, "Free Market of Multi-leader Multi-follower Mobile Crowdsensing: An Incentive Mechanism Design by Deep Reinforcement Learning," IEEE Transactions on Mobile Computing, 2020.
Yufeng Zhan, Peng Li, Kun Wang, Song Guo, and Yuanqing Xia, "Big Data Analytics by CrowdLearning: Architecture and Mechanism Design," IEEE Network, 2020.
Jianting Zhang, Zicong Hong, Xiaoyu Qiu, Yufeng Zhan, Song Guo, and Wuhui Chen, "SkyChain: A Deep Reinforcement Learning-Empowered Dynamic Blockchain Sharding System," in Proc. of ACM ICPP, 2020. (Best Paper Award Running Up)
Yufeng Zhan and Jiang Zhang, "An Incentive Mechanism Design for Efficient Edge Learning by Deep Reinforcement Learning Approach," in Proc. of IEEE INFOCOM, 2020.
Yufeng Zhan, Peng Li, and Song Guo, "Experience-driven Computational Resource Allocation of Federated Learning by Deep Reinforcement Learning," in Proc. of IEEE IPDPS, 2020.
Yufeng Zhan, Peng Li, Zhihao Qu, Deze Zeng, and Song Guo, "A Learning-based Incentive Mechanism for Federated Learning," IEEE Internet of Things Journal, 2020. (ESI Highly Cited Paper)
Yufeng Zhan, Yuanqing Xia, Jiang Zhang, Ting Li, and Yu Wang "An Incentive Mechanism Design for Mobile Crowdsensing with Demand Uncertainties," Information Sciences, 2020.
Chi Harold Liu, Zheyu Chen, and Yufeng Zhan, "Energy-efficient Distributed Mobile Crowd Sensing: A Deep Learning Approach," IEEE Journal on Selected Areas in Communications, 2019.
Yufeng Zhan, Jiang Zhang, Peng Li, and Yuanqing Xia, "Crowdtraining: Architecture and Incentive Mechanism for Deep Learning Training in the Internet of Things," IEEE Network, 2019.
Yufeng Zhan, Yuanqing Xia, Yang Liu, Fan Li, and Yu Wang, "Incentive-Aware Time-Sensitive Data Collection in Mobile Opportunistic Crowdsensing," IEEE Transactions on Vehicular Technology, 2017.
Yufeng Zhan, Yuanqing Xia, Jinhui Zhang, and Yu Wang, "Incentive Mechanism Design in Mobile Ppportunistic Data Collection with Time Sensitivity," IEEE Internet of Things Journal, vol. 5, no. 1, pp. 246-256, 2017.
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