Dr. Jiwei Xu

Time：2023-05-31Views：15

Dr. Jiwei Xu


Associate Professor,

Email: jiwei.xu@buct.edu.cn


Background                                                                  

Associate Professor Jiwei Xu obtained a Ph.D. degree from the Institute of Software, Chinese Academy of Sciences, and worked as a postdoctoral fellow at the School of Computer Science, University College Dublin in Ireland before returning to China. The applicant has led or participated in several key research projects, including one National Natural Science Foundation of China (NSFC) Youth Project, one sub-project of the National Key Research and Development Program, and has been involved as a key researcher in multiple projects funded by the NSFC. He has been invited to serve as a session chair at international conferences such as COMPSAC and Cloud, as well as a reviewer for computer systems and software journals, including the Journal of Systems and Software. He has also served as a project reviewer for the National Natural Science Foundation of China and as an executive member of the Computer Applications Special Committee of the China Computer Federation (CCF).

Areas of Research of Expertise

He has been dedicated to research in various fields related to computer science, such as cloud computing, big data, and software engineering. Focusing on key issues like data value mining and system performance optimization. The research has specifically addressed challenges, including incomplete and inconsistent, complex spatiotemporal, and low performance efficiency problems in data distribution, backup, and deduplication processes in cloud computing environments.

Memberships

  • Member of Chinese Computer Foundation

  • Executive committee member of CCF Computer Applications

Teaching                                             

  • Linux Kernel Programming

  • Principles of Distributed System

  • Object-Oriented Programming

Research                                                

Research Projects

  • 04/2019—01/2023CONSUS: Digital Agriculture

Yield data, Satellite data, Sensor data, Historical data fusion, processing, analysis, clustering, etc.;

Machine Learning based variable rate application;

Micro-service architecture design and implementation.

  • 01/2017—12/2019 Container Image Distribution Optimizing

Multi-version container image loading based on chunk multiplexing;

Container image loading strategy decision based on decision tree;

Dockerfile temporary file error detection

  • 01/2013—12/2016 OnceCloud — IaaS Cloud Platform

Deduplication backup, restoration and optimization of virtual machine images, etc.

  • 09/2010—12/2012 OnceAS — Application Server for PaaS

Jetty application server improvement for PaaS platform (class loader filter of unsafe classes), etc.

  • 09/2008—06/2010 RGPS — Service based internet software building model

Software requirement acquisition and analysis: from natural language to structural model, etc.

Publications                                           

  • J. Xu, N. V. Bermeo, M. O’Grady, and G. M. O’Hare, “Autonomous sensing at the edge,” in 19th IEEE International Conference on Software Architecture(ICSA 2022). IEEE, 2022.

  • T. Wang, W. Zhang, J. Xu, and Z. Gu, “Workflow-aware automatic fault diagnosis for microservice-based applications with statistics,” IEEE Transactions on Network and Service Management, vol. 17, no. 4, 2020.

  • J. Xu, Y. Wu, Z. Lu, and T. Wang, “Dockerfile tf smell detection based on dynamic and static analysis methods,” in 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC). IEEE, 2019.

  • Z. Lu, Y. Wu, J. Xu, and T. Wang, “An acceleration method for docker image update,” in 2019 IEEE International Conference on Fog Computing (ICFC). IEEE, 2019, pp. 15–23.

  • T. Wang, J. Xu, W. Zhang, Z. Gu, and H. Zhong, “Self-adaptive cloud monitoring with online anomaly detection,” Future Generation Computer Systems, vol. 80, pp. 89–101, 2018.

  • J. Xu, T. Wang, X. Xing, W. Zhang, and H. Zhong, “Efficient image restoration of virtual machines with reference count based rewriting and caching,” Future Generation Computer Systems, vol. 77, pp. 87–96, 2017.

  • J. Xu, X. Xing, T. Wang, Z. Lu, and W. Zhang, “Refcre: A reference count based rewriting framework for vm image restoration,” in 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), IEEE, 2017, pp. 473–482.  

  • J. Xu, W. Zhang, Z. Zhang, T. Wang, and T. Huang, “Clustering based acceleration for virtual machine image deduplication in the cloud environment,” Journal of Systems and Software, vol. 121, pp. 144–156, 2016.

  • J. Xu, W. Zhang, S. Ye, J. Wei, and T. Huang, “A lightweight virtual machine image deduplication backup approach in cloud environment,” in 2014 IEEE 38th Annual Computer Software and Applications Conference. IEEE, 2014, pp. 503–508.

  • T. Wang, J. Xu, W. Zhang, J. Zhang, J. Wei, and H. Zhong, “Reseer: Efficient search-based replay for multiprocessor virtual machines,” Journal of Systems and Software, vol. 126, pp. 101–112, 2017.

  • T. Wang, J. Xu, J. Wei, H. Zhong, and Z. Wen-Bo, “A survey of fault detection for distributed software systems with statistical monitoring in cloud computing,” Chin J Comput, vol. 40, no. 2, pp. 397–413, 2017.

  • F. Zhu, J. Liu, S. Wang, J. Xu, L. Xu, J. Ren, D. Ye, J. Wei, and T. Huang, “Hug the elephant: Migrating a legacy data analytics application to hadoop ecosystem,” in 2016 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 2016, pp. 177–187.

  • T. Wang, J. Zhang, W. Zhang, J. Xu, and J. Wei, “Efficient search-based automatic execution replay for virtual machines,” in Asia-Pacific Services Computing Conference. Springer, Cham, 2015, pp. 181–194.