学术报告第201954期

报告题目: Cloud Elasticity

报 告 人: Dr. Jingpeng Li, Reader, School of Natural Sciences, University of Stirling, United Kingdom

报告时间：2019年8月13日15:30—16:30

内容摘要:The elasticity in cloud is essential to the effective management of computational resource as it enables readjustment at runtime to meet application demands. Over the years, researchers and practitioners have proposed many auto-scaling solutions using versatile techniques ranging from simple if-then-else based rules to sophisticated optimisation, control theory and machine learning based methods. However, despite an extensive range of existing elasticity research, the aim of implementing an efficient scaling technique that satisfies the actual demands is still a challenge to achieve. In this paper, we aim to address the challenge using a holistic biologically-inspired feedback switch controller. This approach utilises multiple controllers and a switching mechanism, implemented using fuzzy system that realises the selection of suitable controller at runtime. The fuzzy system also facilitates the design of qualitative elasticity rules. Furthermore, to improve the possibility of avoiding the oscillatory behaviour (a problem commonly associated with switch methodologies), we integrate a biologically-inspired computational model of action selection. Lastly, we use some real workload patterns to evaluate the performance of the proposed approach against the state-of-the-art approaches.

报告人简介:Jingpeng Li is a Reader at the Division of Computer Science and Mathematics, University of Stirling, UK. He received the MSc degree from Huazhong University of Science and Technology (China) in 1998, and the PhD degree from University of Leeds (UK) in 2002. He joined the University of Bradford (UK) as a Research Assistant in 2003. He then worked at the University of Nottingham (both the UK and China campuses) as Research Fellow, Senior Research Fellow and Assistant Professor in 2004-2013.

Dr Li has publishes widely in the areas of Scheduling, Metaheuristics, Machine Learning, Image Processing, Cloud Computing, Sentiment Analysis, and Software Engineering. He has authored over 50 research papers, the majority of which are journal papers published in high impact international journals (e.g., Evolutionary Computation, IEEE Transactions on Evolutionary Computation, European Journal of Operational Research, Transportation Research, Knowledge-Based systems, etc.).

Dr Li is also an active member in the international research community. Apart from organising sessions in various international workshops/conferences, he is serving as the Associate Editors for international journals (e.g., Cognitive Computation, and Big Data Analytics), the Programme Committee members for over 10 international conference, and reviewers for more than 20 prestigious SCI journals.