《Review and Case Study of Network Control and Machine Learning》

Publisher:网络空间安全学院Release Time:2019-04-10Times Views:27

Lecturer: Xu Du

Date and Time: 13:30, April 12, 2019

Venue: Conference Room 142, Computer Building<

About the reporter:

Xu Du graduated from Southeast University in 1990 and gained Master Degree and Doctoral Degree at University of Electronic Science and Technology of China (UESTC) in 1995 and 1998 respectively. Xu is a professor and doctoral supervisor of School of Communication & Information Engineering, UESTC. His research fields include switched network and core routing technology, SDN and network virtualization, and network security technology. He is also a reviewer of many renowned academic journals both at home and abroad as well as a peer evaluation expert of projects. In recent years, he has completed over 20 programs including projects supported by the National Natural Science Foundation, National 973 Project, National 863 Project as well as provincial and ministerial programs. He has also published more than 90 papers in renowned domestic and overseas journals and at international conferences and applied over 20 national invention patents.


Confronted with the increasingly complex network environment and diversified user demand, the network control mode is undergoing profound changes. From providing basic connectivity to meeting SLAs and to the knowledge-defined network and self-driving network, a variety of new concepts and technologies constantly emerges. Among them, machine learning plays an important role and is promising to be the cornerstone of intelligent control of the next-generation network. This report simply sorts out the technologies of network control and machine learning and clarifies the technological development vein. Moreover, methods of the application of machine learning to network control are put forward based on parts of our own work.