Publications   [] [By Topic] [By Year]     

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* = corresponding author of the paper with students or team members supervised by me. '= co-first authors with equal contribution by alphabetical order. # = authors in alphabetical order    

Distributed and Parallel Computing

• M. Zhang, G. Li, C. Guo, R. Yang*, S. Wang, H. Bao, X. Li, M. Xu, T. Wo, C. Hu. SuperFE: A Scalable and Flexible Feature Extractor for ML-based Traffic Analysis Applications. in the 20th ACM EuroSys 2025

• Z. Liu, R. Yang*, J. Ouyang, W. Jiang, T. Ye, M. Zhang, S. Huang, J. Huang, C. Song, D. Zhang, T. Wo, C. Hu. KALE: Elastic GPU Scheduling for Online DL Model Training. in the 15th ACM SoCC 2024

• R. Yang and J. Xu. Resilient QoS-Aware Workload Co-Scheduling and User Anomaly Detection in Shared Computing Clusters, the UK Alan Turing Institute Workshop on Edge-Cloud Infrastructure for Distributed Intelligent Computing, 2023

• Z. Wen, R. Yang*, B. Qian, Z. Wang, H. Peng, J. Xu, A.Y. Zomaya, R. Ranjan. Janus: Latency-Aware Traffic Scheduling for IoT Data Streaming in Edge Environments. IEEE Trans. on Services Computing (TSC), 2023

• R. Yang', J. Zhu', X. Sun, T. Wo, C. Hu, H. Peng, J. Xiao, A. Y. Zomaya, J. Xu. QoS-Aware Co-Scheduling for Distributed Long-Running Applications on Shared Clusters, IEEE Trans. on Parallel and Distributed Systems (TPDS), 2022

• Y. Song, L. Jiao, R. Yang, T. Wo and J. Xu. Incentivizing Online Content Caching in Distributed Edge Networks via Auction-Based Subsidization. 19th IEEE International Conference on Sensing, Communication, and Networking (SECON), 2022

• X. Sun, W. Wang, S. Qiu, R. Yang, S. Huang, J. Xu, Z. Wang. STRONGHOLD: Fast and Affordable Billion-scale Deep Learning Model Training. IEEE/ACM SC 2022

• G. Yeung, B. Borowiec, R. Yang*, A. Friday, R. Harper, P. Garraghan. Horus: Interference-aware and Prediction-based Scheduling in Deep Learning Systems. IEEE Trans. on Parallel and Distributed Systems (TPDS), 2021

• R. Yang, C. Hu, X. Sun, P. Garraghan, T. Wo, Z. Wen, H. Peng, J. Xu and C. Li. Performance-aware Speculative Resource Oversubscription for Large-scale Clusters, IEEE Trans. on Parallel and Distributed Systems (TPDS), 2020

• C. Mommessin', R. Yang'*, N. Shakhlevich, X. Sun, S. Kumar, J. Xiao, J. Xu. Affinity-Aware Resource Provisioning for Long-Running Applications in Shared Clusters. Journal of Parallel and Distributed Computing (JPDC), 2023

• R. Yang', J. Zhu', C. Hu, T. Wo, S. Xue, J. Ouyang and J. Xu. Perphon: a ML-based Agent for Workload Co-location via Performance Prediction and Resource Inference. ACM Symposium on Cloud Computing (SoCC), 2019

• X.Sun, C. Hu, R. Yang*, P. Garraghan, T. Wo, J. Xu, J. Zhu, C. Li. ROSE: Cluster Resource Scheduling via Speculative Over-subscription. in the 38th IEEE ICDCS 2018

• Z. Zhang, C. Li, Y.Tao, R. Yang*, H. Tang, J. Xu. Fuxi: a Fault-Tolerant Resource Management and Job Scheduling System at Internet Scale, in the 40th VLDB 2014,

• X. Sun, C. Hu, R. Yang*, P. Garraghan, C. Li. ROSE: Cluster Scheduling through Efficient Resource Overselling, ACM/USENIX SOSP, 2017 (poster)

• R. Yang', J. Zhu', C. Hu, T. Wo, S. Xue, J. Ouyang, J. Xu. Perph: A Workload Co-location Agent with Online Performance Prediction and Resource Inference. IEEE/ACM CCGRID 2021

• R. Yang, Z. Wen, D. McKee, T. Lin, J. Xu and P. Garraghan. Software-Defined Fog Orchestration for IoT Services. Book Chapter, Fog and Fogonomics Challenges and Practices, Wiley, ISBN: 978-1-119-50109-1 [link] [googlebook] [preprint]

• Z. Wen, R. Yang*, P. Garraghan, T. Lin, J. Xu and M. Rovatsos. Fog Orchestration for IoT Services, in IEEE Internet Computing (IC), IEEE Computer Society (SCI-IF = 1.929, Q1) (Highly Cited Paper)

• G. Yeung, B. Borowiec, R. Yang*, A. Friday, R. Harper, P. Garraghan. Horus: An Interference-aware Resource Manager for Deep Learning Systems. International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP), 2020

• C. Hu, J. Zhu, R. Yang*, H. Peng, T. Wo, S. Xue, X. Yu, J. Xu, R. Ranjan. Toposch: Latency-Aware Scheduling Based on Critical Path Analysis on Shared YARN Clusters. IEEE Conference on Cloud Computing (Cloud), 2020

• R. Yang, X. Ouyang, Y. Chen, P. Townend, J. Xu. Intelligent Resource Scheduling: a Machine Learning Perspective. in the 12th IEEE SOSE 2018,

• S. Kumar, R. Yang, R. Singh, R. Bahsoon, J. Xu, R. Buyya. MatchCom: Stable Matching-Based Software Services Composition in Cloud Computing Environments. The 24th International Conference on Web Engineering (ICWE), 2024

• N. V. Shakhlevich, T. Erlebach, C. Mommessin, R. Yang, X. Sun, S. Kumar, J. Xiao, J. Xu. Vector Bin Packing for Resource Management in Distributed Systems: A Case Study. The 19th International Workshop on Project Management and Scheduling (PMS). The Association of European Operational Research Societies. 2024

• T. Erlebach#, S. Kumar, C. Mommessin, N. V. Shakhlevich, X. Sun, J. Xiao, J. Xu, R. Yang#. Affinity Aware Scheduling in Distributed Computing via Vector Bin Packing. The 33rd European Conference on Operational Research (EURO 2024 Copenhagen).

• J. Wang, G. Wang, T. Wo, X. Wang and R. Yang*. RESCAPE: A Resource Estimation System for Microservices with Graph Neural Networks and Profile Engine. The 15th IEEE Joint Cloud Conference (JCC) (Best Paper Award)

• W. Peng, J. Wang, T. Wo and R. Yang*. PrecisionProbe: Non-intrusive Performance Analysis Tool for Deep Learning Recommendation Models. The 15th IEEE Joint Cloud Conference (JCC)

• R. Yang. Efficient and Reliable Resource Scheduling at Internet Scale: Theory and Practice, PhD. thesis, 2017 (with Honor, Outstanding Graduate Award of Beijing Graduates)

• R. Yang and J. Xu. Computing at Massive Scale: Scalability and Dependability Challenges, in the 10th IEEE International Symposium on Service Oriented System Engineering (SOSE 2016)

• Y. Wang, R. Yang, T. Wo, W. Jiang, C. Hu. Improving Utilization through Dynamic VM Resource Allocation in Hybrid Cloud Environment, in the 20th IEEE ICPADS 2014,

• W. Wang, C. Hu, T. Wo and R. Yang*. YarnPlus: A Yarn Based Framework for Fine-Grained Resource Sharing in Heterogeneous Computing Environments, in the 11th CCF CNCC 2013,

• S. Xue, C. Hu, J. Zhu, R. Yang*. Shaready: A Resource-Isolated Workload Co-location System. in the 13th IEEE SOSE, 2019

System Dependability

• Y. Zhao, M. Zhang, T. Wo, R. Yang, C. Hu. BTDefense: A Priority-Aware Adaptive Strategy Against the Block Table Overflow Attack in vLLM. The 30th Symposium on Operating Systems (SOSP), 2024, poster

• R. Wang, X. Mou, R. Yang*, K. Gao, P. Liu, C. Liu, T. Wo and X. Liu. CutAddPaste: Time Series Anomaly Detection by Exploiting Abnormal Knowledge. The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024

• X. Sun, Q. Ye, H. Hu, J. Duan, T. Wo, J. Xu and R. Yang. LDPRecover: Recovering Frequencies from Poisoning Attacks against Local Differential Privacy. IEEE International Conference on Data Engineering (ICDE), 2024

• L. He, Y. Yang, Q. Wu, H. Liu, R. Yang, X. Wang, H. Peng, Y. Liao, P. Zhou. BotDGT: Dynamicity-aware Social Network Bot Detection with Dynamic Graph Transformers. The 33rd International Joint Conference on Artificial Intelligence (IJCAI), 2024

• T. Li, Z. Hong, Q. Cai, L. Yu, Z. Wen, and R. Yang*. BISSIAM: Bispectrum Siamese Network Based Contrastive Learning for UAV Anomaly Detection, IEEE Trans. on Knowledge and Data Engineering (TKDE), 2021

• Y. Hei', R. Yang', H. Peng, L. Wang, X. Xu, J. Liu, H. Liu, J. Xu, L. Sun. Hawk: Reliable Android Malware Detection through Heterogeneous Graph Neural Network. IEEE Trans. on Neural Networks and Learning Systems (TNNLS), 2021

• Y. Song, T. Wo, R. Yang*, Q. Shen and J. Xu. Joint Optimization of Cache Placement and Request Routing in Unreliable Networks. Journal of Parallel and Distributed Computing (JPDC), 2021

• Z. Wen, T. Lin, R. Yang*, S. Ji, R. Ranjan, A. Romanovsky, C. Lin, J. Xu. GA-Par: Dependable Microservice Orchestration Framework for Geo-Distributed Clouds, IEEE Trans. on Parallel and Distributed Systems (TPDS), 2019 [full version]

• R. Yang, Y. Zhang, P. Garraghan, Y. Feng, J. Ouyang, J. Xu, Z. Zhang, C. Li. Reliable Cloud Service in Massive-scale Systems through Effective Low-cost Failover. in IEEE Trans. on Services Computing (TSC), 2017 (IF=11.02, CCF-A)

• P. Garraghan, X. Ouyang, R. Yang*, D. McKee, J. Xu. Straggler Root-cause and Impact Analysis for Massive-scale Virtualized Cloud Datacenters, in IEEE Trans. on Services Computing (TSC), 2017 (IF=11.02, CCF-A) (Highly Cited Paper)

• X. Ouyang, P. Garraghan, R. Yang, P. Townend, and J. Xu. Reducing Late-Timing Failure at Scale: Straggler Root-Cause Analysis in Cloud Datacenters, in the 46th IEEE/IFIP DSN 2016 (short)

• P. Garraghan, R. Yang*, Z. Wen, A. Romanovsky, J. Xu, R. Buyya, R. Ranjan. Emergent Failures: Rethinking Cloud Reliability at Scale. IEEE Cloud Computing, 2018 (SCI-IF = 2.929, Q1)

• L. Cui, J. Li, T. Wo, B. Li, R. Yang, Y. Cao, J. Huai. HotRestore: A Fast Restore System for Virtual Machine Cluster, in the 28th USENIX Large Installation System Administration Conference (LISA 2014)

• R. Yang, T. Wo, C. Hu, J. Xu and M. Zhang. D2PS : a Dependable Data Provisioning Service in Multi-tenants Cloud Environment. in the 17th IEEE HASE 2016

• X. Ouyang, C. Wang, R. Yang, P. Townend, J. Xu. ML-NA: a Machine Learning based Node Performance Analyzer Utilizing Straggler Statistics. In the 23th IEEE ICPADS 2017

• R. Yang, J. Ouyang, C. Hu. Fail at Scale. Communications of CCF, 2016 (In Chinese)

• P. Townend, S. J. Clement, D. Burdett, R. Yang*, J. Shaw, B. Slater, J. Xu. Improving Data Center Efficiency Through Holistic Scheduling In Kubernetes. in the 13th IEEE SOSE, 2019

• Y. Li, X. Sun , R. Yang* , X. Sun, S. Chen, S. Wang, A. Bhuiyan, A. Y. Zomaya, J. Xu. GNNRI: detecting anomalous social network users through heterogeneous information networks and user relevance exploration. in the International Journal of Machine Learning and Cybernetics, 2024

Deep Learning Systems and Applications

• H. Wang, R. Yang*, J. Sun, H. Peng, X. Mou, T. Wo and X. Liu. IOP: An Idempotent-Like Optimization Method on the Pareto Front of Hypernetwork. The 39th AAAI Conference on Artificial Intelligence (AAAI), 2025

• Y. Yang, Q. Wu, B. He, H. Peng, R. Yang, Z. Hao, Y. Liao. SEBot: Structural Entropy Guided Multi-View Contrastive learning for Social Bot Detection. The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024

• B. Qian, Y. Xuan, D. Wu, Z. Wen, R. Yang, S. He, J. Chen, and R. Ranjan. Edge-Cloud Collaborative Streaming Video Analytics with Multi-agent Deep Reinforcement Learning. IEEE Network. 2024

• Q. Wu, Y. Yang, H. Liu, R. Yang, Y. Liao, P. Zhou. BotSCL: Heterophily-aware Social Bot Detection with Supervised Contrastive Learning. The 27th International Conference on Pattern Recognition (ICPR)

• J. Zhao, R. Yang, S. Qiu, Z. Wang. Unleashing the Potential of Acquisition Functions in High Dimensional Bayesian Optimization. Transactions on Machine Learning Research (TMLR), 2024

• Y. Yang, R. Yang*, H. Peng, Y. Li, T. Li, Y. Liao, P. Zhou. FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection. ACM WWW 2023

• R. Yang', Y. Yang', Y. Li, K. Cui, Z. Yang, Y. Wang, J. Xu, H. Xie. RoSGAS: Adaptive Social Bot Detection with Reinforced Self-supervised GNN Architecture Search. Transactions on the Web (TWEB), 2022

• D. Zou, H. Peng, X. Huang, R. Yang, J. Li, J. Wu, C. Liu, P. S. Yu. SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization. ACM WWW 2023

• J. Zhao, R. Yang, S. Qiu, Z. Wang. Enhancing High-dimensional Bayesian Optimization by Optimizing the Acquisition Function Maximizer Initialization. arXiv Preprint, arXiv:2302.08298, 2023

• Z. Wen, H. Hu, R. Yang*, B. Qian, R. Sham, R. Sun, J. Xu, P. Patel, O. Rana, S. Dustdar, R. Ranjan. Orchestrating Networked Machine Learning Applications using Autosteer. IEEE Internet Computing, 2022

• H. Peng, R. Yang, Z. Wang, J. Li, L. He, P. S. Yu, A. Y. Zomaya, R. Ranjan. LIME: Low-Cost and Incremental Learning for Dynamic Heterogeneous Information Networks. IEEE Trans. on Computers (TC), 2021

• H. Peng, J. Li, Y. Song, R. Yang, R. Ranjan, P. S. Yu, L. He. Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks, ACM Trans. on Knowledge Discovery from Data (TKDD), 2021

• H. Peng, R. Zhang, Y. Dou, R. Yang, J. Zhang, and P. S. Yu. Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks, ACM Trans. on Information Systems (TOIS), 2021 (Hot Paper in ESI)

• Q. Li, H. Peng, J. Li, C. Xia, R. Yang, L. Sun, P. S. Yu, L. He. A Survey on Text Classification: from Traditional to Deep Learning. ACM Trans. on Intelligent Systems and Technology (TIST) (Highly Cited Paper)

• H. Peng, J. Li, Z. Wang, R. Yang, M. Liu, M. Zhang, P. S. Yu, L. He. Lifelong Property Price Prediction: A Case Study for The Toronto Real Estate Market. IEEE Trans. on Knowledge and Data Engineering (TKDE)

• B. Qian, J. Su, Z. Wen, D.N. Jha, Y. Li, Y. Guan, D. Puthal, P. James, R. Yang, A. Y. Zomaya, O. Rana, L. Wang, R. Ranjan. Orchestrating Development Lifecycle of ML-Based IoT Applications: a Survey. ACM Computing Surveys (CSUR), 2020

• H. Peng, J. Li, S. Wang, L. Wang, Q. Gong, R. Yang, B. Li, L. He and P. S. Yu. Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification. IEEE Trans. on Knowledge and Data Engineering (TKDE), 2019 (Highly Cited Paper)

Early Work on Big Data and Virtualized Execution Environment

• R. Yang, Z. Zhao, J. Ouyang, J. Xu. Cloud Evolution: Enterprise-Wide Digitalization over Clouds. Book Chapter, World Scientific Reference on Digital Data-Centric Platforms in the Age of IoT (invited chapter and in press)

• Y. Zhang, M. Zhang, T. Wo, X. Lin, R. Yang, J. Xu. A Scalable lnternet-of-Vehicles Service over Joint Clouds. in the 9th IEEE JCC 2018

• T. Wo, R. Yang, Y. Wang, C. Hu and J. Xu. Software-defined Storage in Joint Cloud. Communications of CCF, 2017 (In Chinese)

• L. Du, T. Wo, R. Yang*, C. Hu. Cider: a Rapid Docker Container Deployment System through Sharing Network Storage. in the 19th IEEE HPCC 2017

• C. Hu, X. Wang, R. Yang and T. Wo. ScalaRDF: a Distributed, Elastic and Scalable In-Memory RDF Triple Store. in the 22th IEEE ICPADS 2016

• H. Wang, M. Zhang, R. Yang, X. Lin, T. Wo, R. Ranjan and J. Xu. SMTP: An Optimized Storage Model For Big Vehicle Trajectory Data Exploiting Trajectory Pattern. in the18th IEEE HPCC 2016,

• J. Wen, T. Wo, M. Zhang, R. Yang, J. Xu A Method for Private Car Transportation Dispatching Based on a Passenger Demand Model. in the 2nd International Conference on Internet of Vehicles (IoV 2015),

• P. Liu, R. Yang*, J. Sun, X. Liu. SysOptic: A Fine-Grained Monitoring System for Virtual Machines Based on PMU. in the 13th IEEE SOSE, 2019

• Y. Huang, R. Yang, L. Cui, T. Wo, C. Hu, B. Li. VMCSnap: Taking Snapshots of Virtual Machine Cluster with Memory Deduplication. in the 8th IEEE SOSE 2014

• J. Li, J.Zheng, L. Cui and R. Yang. ConSnap: Taking Continuous Snapshots for Running State Protection of Virtual Machines, in the 20th IEEE ICPADS 2014,

• B. Zhang, J. Kang, T. Wo, Y. Wang, R. Yang. a Flexible and Scalable Affinity Lock for the Kernel, in the 16th IEEE HPCC 2014,

• I. Moreno, R. Yang, J. Xu, T. Wo. Improved Energy-Efficiency in Cloud Datacenters with Interference-Aware Virtual Machine Placement. in the 11th IEEE ISADS 2013 (Best Paper Award)

• R. Yang, I. Moreno, J. Xu, T. Wo. An Analysis of Performance Interference Effects on Energy-Efficiency of Virtualized Cloud Environments, in the IEEE CloudCom 2013,

• Y. Zhang, R. Yang, T. Wo, C. Hu, J. Kang , L. Cui. CloudAP: Improving the QoS of Mobile Applications with Efficient VM Migration, in the 15th IEEE HPCC 2013,