1. Highly parallel cloud services
Rui Han, Siguang Huang, Zhentao Wang, and Jianfeng Zhan. “CLAP: Component-level Approximate Processing for Low Tail Latency and High Result Accuracy in Cloud Online Services.” In IEEE Transactions on Parallel and Distributed Systems (TPDS), IEEE, volume 28, issue. 8, pp 2190 - 2203, 2017. (CCF A)
Rui Han, Siguang Huang, Fei Tang, Fugui Chang, and Jianfeng Zhan. AccuracyTrader: Accuracy-aware Approximate Processing for Low Tail Latency and High Result Accuracy in Cloud Online Services. In: The 45th International Conference on Parallel Processing (ICPP 2016), Philadelphia, PA, USA. IEEE Press. pp. 278-287. IEEE, 2016. (CCF B)
Rui Han, Junwei Wang, Siguang Huang, Chenrong Shao, Shulin Zhan, Jianfeng Zhan and Jose Luis Vazquez-Poletti. PCS: Predictive Component-level Scheduling for Reducing Tail Latency in Cloud Online Services. In: The 44th International Conference on Parallel Processing (ICPP 2015), Beijing, China. IEEE Press. pp. 490-499. IEEE, 2015. (CCF B)
Zhao J, Rui Han, Yang Y, et al. Federated learning with heterogeneity-aware probabilistic synchronous parallel on edge[J]. IEEE Transactions on Services Computing, 2021, 15(2): 614-626.(CCF A)
Luopan Y, Rui Han*, Zhang Q, et al. Fedknow: Federated continual learning with signature task knowledge integration at edge[C]//2023 IEEE 39th International Conference on Data Engineering (ICDE). IEEE, 2023: 341-354. (CCF A)
Zuo X, Luopan Y, Rui Han*, et al. FedViT: Federated continual learning of vision transformer at edge[J]. Future Generation Computer Systems, 2024, 154: 1-15.
2. Edge Intelligence and Big Data Analytics in the Cloud (* corresponding author)
Rui Han, Q. Zhang, C. H. Liu, G. Wang, J. Tang, Lydia Y. Chen. LegoDNN: Block-grained Scaling of Deep Neural Networks for Mobile Vision. In: ACM MOBICOM 2021, New Orleans, United States. pp. 406-419, ACM, 2021. (CCF A)
Rui Han, C. H. Liu, S. Li, L. Chen, G. Wang, J. Tang and J. Ye. SlimML: Removing Non-critical Input Data in Large-scale Iterative Machine Learning. In: IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume: 33, Issue: 5, Page(s): 2223-2236, 2021. (CCF A)
Rui Han, C. H. Liu, S. Li, S. Wen, and X. Liu. Accelerating Deep Learning Systems via Critical Set Identification and Model Compression. In: IEEE Transactions on Computers (TC), Volume: 69, Issue:7, Page(s): 1059-1070, July 2020. (CCF A)
Rui Han, Dong Li, Junyan Ouyang, Chi Harold Liu, Guoren Wang, Dapeng Wu，Lydia Y. Chen. Accurate Differentially Private Deep Learning on the Edge. In: IEEE Transaction on Parallel and Distributed Systems (TPDS), volume 32, issue. 9, Page(s): 2231 - 2247, 2021. (CCF A)
Zhao, Z., Birke, R., Rui Han*, R., Robu, B., Bouchenak, S., Mokhtar, S. B., and Lydia Y. Chen. Enhancing Robustness of On-line Learning Models on Highly Noisy Data. In: IEEE Transactions on Dependable and Secure Computing （TDSC), 2021, in press. (CCF A)
Rui Han, S. Li, S. Xiang, C. H. Liu*, G. Xin, Lydia Y. Chen. Accelerating Gossip-based Deep Learning in Heterogeneous Edge Computing Platforms. In: IEEE Transaction on Parallel and Distributed Systems (TPDS), volume 32, issue. 7, Page(s): 1591-1602, 2020. (CCF A)
Rui Han, Fan Zhang, and Zhentao Wang. AccurateML: Information-aggregation-based Approximate Processing for Fast and Accurate Machine Learning on MapReduce. In: IEEE International Conference on Computer Communications (INFOCOM 2017), Atlanta, GA, USA. IEEE Press. (CCF A)
Rui Han, Zhang F, Chen L Y, et al. Work-in-progress: Maximizing model accuracy in real-time and iterative machine learning[C]//2017 IEEE Real-Time Systems Symposium (RTSS). IEEE, 2017: 351-353. (CCF A poster)
Q. Zhang, Rui Han*, Gaofeng Xin, Guoren Wang, C. H. Liu, Lydia Y. Chen. Lightweight and Accurate DNN-based Anomaly Detection at Edge. In: IEEE Transaction on Parallel and Distributed Systems (TPDS), 2021, early access. (CCF A).
Zipeng Dai, Hao Wang, C. H. Liu*, Rui Han, Jian Tang, and Guoren Wang. Mobile Crowdsensing for Data Freshness: A Deep Reinforcement Learning Approach. In: IEEE International Conference on Computer Communications (INFOCOM 2021), IEEE Press. (CCF A)
Zipeng Dai, Hao Wang, C. H. Liu*, Rui Han, Guoren Wang, Kin K. Leung, and Jian Tang. Delay-Sensitive Energy-Efficient UAV Crowdsensing by Deep Reinforcement Learning. In: IEEE Transactions on Mobile Computing (TMC), 2021, IEEE Press. (CCF A)
Y. Wang, C. H. Liu*, C. Piao, Y. Yuan, Rui Han, G. Wang, “Human-Drone Collaborative Spatial Crowdsourcing by Memory-Augmented and Multi-Agent Deep Reinforcement Learning,” in IEEE ICDE 2022 , virtual, May 9-12 2022. (CCF A)
Z. Dai, C. H. Liu*, Y. Ye, Rui Han, Y. Yuan, G. Wang, J. Tang, “AoI-minimal UAV Crowdsensing by Model-based Graph Convolutional Reinforcement Learning,” in IEEE INFOCOM 2022 , Virtual, 2-5 May, 2022. (CCF A)
Zong Z, Wen L, Hu X, Rui Han, et al. Mespaconfig: Memory-sparing configuration auto-tuning for co-located in-memory cluster computing jobs[J]. IEEE Transactions on Services Computing, 2021, 15(5): 2883-2896. (CCF A)
Zhang Q, Rui Han*, Liu C H, et al. EdgeVisionBench: A benchmark of evolving input domains for vision applications at edge[C]//2023 IEEE 39th International Conference on Data Engineering (ICDE). IEEE, 2023: 3643-3646. (CCF A demo)
Zhang Q, Rui Han*, Liu C H, et al. ElasticDNN: On-Device Neural Network Remodeling for Adapting Evolving Vision Domains at Edge[J]. IEEE Transactions on Computers, 2024. (CCF A)
3. Cloud Job Scheduling and Application Scaling
Rui Han, S. Wen, C. H. Liu, Y. Yuan, G. Wang, L. Y. Chen. EdgeTuner: Fast Scheduling Algorithm Tuning for Dynamic Edge-Cloud Workloads and Resources. In: IEEE INFOCOM 2022. 2022. (CCF A)
Rui Han, C. H. Liu, Z. Zong, Lydia Y. Chen, W. Liu, S. Wang, J. Zhan. Workload-adaptive Configuration Tuning for Hierarchical Cloud Schedulers. In: IEEE Transaction on Parallel and Distributed Systems (TPDS), Volume: 30, Issue: 12, Page(s): 2879-2895. 2019. (CCF A)
Rui Han, Z. Zong, Lydia Y. Chen, W. Liu, S. Wang, J. Zhan. AdaptiveConfig: Run-time Configuration of Cluster Schedulers for Cloud Short-running Jobs. ICDCS 2017, Pages 2879 - 2895. (CCF B)
Rui Han, Li Guo, Moustafa M Ghanem, Yike Guo. Lightweight Resource Scaling for Cloud Applications. 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2012), Ottawa, Canada. IEEE Press. pp. 644-651. (CCF C)
Rui Han, Moustafa M. Ghanem, Li Guo, Yike Guo and Michelle Osmond. Enabling Cost-Aware and Adaptive Elasticity of Multi-tier Cloud Applications. In: Future Generation Computer Systems, 32, 82-98, 2014. (CCF C）
J.L. Vazquez-Poletti, R. Moreno-Vozmediano, Rui Han, Weikun Wang, I.M. Llorente. SaaS enabled admission control for MCMC simulation in cloud computing infrastructures. Computer Physics Communications. Volume 211, February 2017, Pages 88–97. (Q1, Impact factor: 3.635).
Schahram Dustdar, Yike Guo, Rui Han, Benjamin Satzger, Hong-Linh Truong.Programming Directives for Elastic Computing. In: IEEE Internet Computing, 16(6), 72-77, 2012. (Impact factor: 2.0).
4. Big data benchmarking
Rui Han, Lizy Kurian John, and Jianfeng Zhan. Benchmarking Big Data Systems: A Review. In: IEEE Transactions on Services Computing (TSC), IEEE, volume 11, issue. 3, pp 580 - 597, 2017. PDF.(Q1, CCF A).
Zhen Jia, Jianfeng Zhan, Lei Wang, Chunjie Luo, Wanling Gao, Yi Jin, Rui Han, and Lixin Zhang . Understanding Big Data Analytics Workloads on Modern Processor. In IEEE Transactions on Parallel and Distributed Systems (TPDS), Volume: 28, Issue: 6, Page(s): 1797-1810, 2016. (CCF A)
Rui Han, Shulin Zhan, Chenrong Shao, Junwei Wang, Lizy K John, Jiangtao Xu, Gang Lu, and Lei Wang. BigDataBench-MT: A Benchmark Tool for Generating Realistic Mixed Data Center Workloads. In: The 2015 ACM Symposium on Cloud Computing conference (SoCC 2015), Kohala Coast, Hawai’i, USA, 2015. (CCF B, post paper)
Rui Han, Xiaoyi Lu, and Jiangtao Xu. On big data benchmarking. In: Workshop on Big Data Benchmarks, Performance Optimization, and Emerging Hardware (BPOE 2014), Salt Lake City, USA, LNCS Press. pp. 3-18. (Selected as the 100 recommended big data papers by PayPal ).
Jianfeng Zhan, Wanling Gao, Lei Wang, Jingwei Li, Kai Wei, Chunjie Luo, Rui Han, Xinhui Tian, Chunyu Jiang. BigDataBench: An Open-source Big Data Benchmark Suite (In Chinese). Chinese Journal of Computers 39 (1), 196-211, 2016. (CCF A-Chinese)
5. Workflow management systems
Rui Han，Yingbo Liu，Lijie WenJianmin Wang: Dynamically analyzing time constraints in workflow systems with fixed-date constraint. In: 12th International Asia-Pacific Web Conference (APWEB 2010):99-105. (CCF C).
Rui Han, Yingbo Liu, Lijie Wen and Jianmin Wang. A Two-Stage Probabilistic Approach to Manage Personal Worklist in Workflow Management Systems. In: OTM’09, 17th International Conference on COOPERATIVE INFORMATION SYSTEMS (CoopIS 2009), Vilamoura, Algarve, Portugal. Published by Springer Verlag, Part I, LNCS 5870, pp. 24–41. (CCF C).
Rui Han, Yingbo Liu, Lijie Wen, Jianmin Wang. A Probabilistic Approach to Analyze and Adjust Time Constraints in Workflow Management System (In Chinese). Journal of Computer Research and Development, 47(1), 157-163, 2010 (Best paper awards at NDBC 2009，CCF A-Chinese)