| Causeinfer: Automatic and distributed performance diagnosis with hierarchical causality graph in large distributed systems P Chen, Y Qi, P Zheng, D Hou IEEE INFOCOM 2014-IEEE Conference on Computer Communications, 1887-1895, 2014 | 70 | 2014 |
| Microscope: Pinpoint performance issues with causal graphs in micro-service environments JJ Lin, P Chen, Z Zheng International Conference on Service-Oriented Computing, 3-20, 2018 | 64 | 2018 |
| Cloudranger: Root cause identification for cloud native systems P Wang, J Xu, M Ma, W Lin, D Pan, Y Wang, P Chen 2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid …, 2018 | 56 | 2018 |
| An approach for anomaly diagnosis based on hybrid graph model with logs for distributed services T Jia, P Chen, L Yang, Y Li, F Meng, J Xu 2017 IEEE international conference on web services (ICWS), 25-32, 2017 | 49 | 2017 |
| Logsed: Anomaly diagnosis through mining time-weighted control flow graph in logs T Jia, L Yang, P Chen, Y Li, F Meng, J Xu 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), 447-455, 2017 | 43 | 2017 |
| An automatic framework for detecting and characterizing performance degradation of software systems P Zheng, Y Qi, Y Zhou, P Chen, J Zhan, MRT Lyu IEEE Transactions on Reliability 63 (4), 927-943, 2014 | 41 | 2014 |
| Microscaler: Automatic scaling for microservices with an online learning approach G Yu, P Chen, Z Zheng 2019 IEEE International Conference on Web Services (ICWS), 68-75, 2019 | 30 | 2019 |
| Automap: Diagnose your microservice-based web applications automatically M Ma, J Xu, Y Wang, P Chen, Z Zhang, P Wang Proceedings of The Web Conference 2020, 246-258, 2020 | 28 | 2020 |
| Taskinsight: A fine-grained performance anomaly detection and problem locating system X Zhang, F Meng, P Chen, J Xu 2016 IEEE 9th International Conference on Cloud Computing (CLOUD), 917-920, 2016 | 28 | 2016 |
| CauseInfer: Automated End-to-End Performance Diagnosis with Hierarchical Causality Graph in Cloud Environment P Chen, Y Qi, D Hou IEEE transactions on services computing 12 (2), 214-230, 2016 | 25 | 2016 |
| ARF-predictor: Effective prediction of aging-related failure using entropy P Chen, Y Qi, X Li, D Hou, MRT Lyu IEEE Transactions on Dependable and Secure Computing 15 (4), 675-693, 2016 | 21 | 2016 |
| Function delivery network: Extending serverless computing for heterogeneous platforms A Jindal, M Gerndt, M Chadha, V Podolskiy, P Chen Software: Practice and Experience 51 (9), 1936-1963, 2021 | 19 | 2021 |
| Swisslog: Robust and unified deep learning based log anomaly detection for diverse faults X Li, P Chen, L Jing, Z He, G Yu 2020 IEEE 31st International Symposium on Software Reliability Engineering …, 2020 | 19 | 2020 |
| Microscaler: Cost-effective scaling for microservice applications in the cloud with an online learning approach G Yu, P Chen, Z Zheng IEEE Transactions on Cloud Computing, 2020 | 16 | 2020 |
| Logdc: Problem diagnosis for declartively-deployed cloud applications with log J Xu, P Chen, L Yang, F Meng, P Wang 2017 IEEE 14th International Conference on e-Business Engineering (ICEBE …, 2017 | 15 | 2017 |
| A spatiotemporal deep learning approach for unsupervised anomaly detection in cloud systems Z He, P Chen, X Li, Y Wang, G Yu, C Chen, X Li, Z Zheng IEEE Transactions on Neural Networks and Learning Systems, 2020 | 14 | 2020 |
| An ensemble MIC-based approach for performance diagnosis in big data platform P Chen, Y Qi, X Li, L Su 2013 IEEE International Conference on Big Data, 78-85, 2013 | 14 | 2013 |
| A framework of virtual war room and matrix sketch-based streaming anomaly detection for microservice systems H Chen, P Chen, G Yu IEEE Access 8, 43413-43426, 2020 | 13 | 2020 |
| Lightweight and adaptive service api performance monitoring in highly dynamic cloud environment J Xu, Y Wang, P Chen, P Wang 2017 IEEE International Conference on Services Computing (SCC), 35-43, 2017 | 13 | 2017 |
| Driftinsight: detecting anomalous behaviors in large-scale cloud platform FJ Meng, X Zhang, P Chen, JM Xu 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), 230-237, 2017 | 9 | 2017 |
