On the afternoon of August 13th, Prof. Jingpeng Li from University of Stirling, United Kingdom, visited School of Artificial Intelligence and Automation and presented a report titled “Cloud Elasticity” in Room 311, South-1 Building. The report was hosted by Prof. Yindong Shen and more than 20 teachers and students attended the report.
At present, Jingpeng Li is a professor in Department of Computer Science and Mathematics of University of Stirling, United Kingdom. He received his master degree in Huazhong University of Science and Technology in 1998 and Ph. D. degree in University of Leeds (UK) in 2002. In 2003, he worked as a research assistant in University of Bradford (UK), and from 2004 to 2013, he worked successively as a researcher, senior researcher and assistant professor in University of Nottingham (campuses in UK and China).
The research interests of Prof. Li include scheduling and metaheuristic method, machine learning, image processing, cloud computing, sentiment analysis and software engineering, and he has made significant academic achievements in these fields. He has published more than 50 research papers, most of them are published in high-impact international journals (such as Evolutionary Computation, IEEE Transactions on Evolutionary Computation, European Journal of Operational Research, Transportation Research, and Knowledge-Based systems). He once organized many important international academic conferences and seminars. Moreover, Prof. Li serves as a member of the procedural committee of more than 10 international conferences, associated editor of some international journals (such as Cognitive Computation and Big Data Analytics), and reviewer of more than 20 famous SCI journals.
In his report, Prof. Li discussed the flexible control problem in the process of cloud computing. Through flexible control on the number of virtual machines used in cloud computing process, not only the cost of virtual machine payment in cloud computing process was reduced, but also the service level of users was greatly improved. First, a fuzzy control system was established by the off-line learning method, and then the number of virtual machines needed was controlled according to the actual situation. The parameters of the control system were obtained by the improved multi-objective genetic algorithm. Its core was to introduce the idea of control into the supply of resources in cloud computing so that the resource allocation in cloud computing process could be flexibly adjusted to obtain the optimal solution. Last, Prof. Li took the user’s website visit request during the World Cup as experimental background to verify the validity of the proposed method through comparative experiments.
Prof. Li’s report expanded the research visions of the audience in cloud computing control, and gave great inspiration to students. After the report, teachers and students expressed their opinions and raised questions enthusiastically and Prof. Li patiently answered them. He also discussed the future development directions in the field. Later, teachers and Professor Li had a more in-depth discussion about the topic.
