2009-12-22云计算, 实验室, 微软亚洲研究院
王海勋博士受聘中国人民大学兼职教授暨学术报告： Relational DBMS for Cloud Computing:
An Eventual Consistency Approach
(Seminar Series on Mobile plus Cloud Computing)
报告题目：Relational DBMS for Cloud Computing: An Eventual Consistency Approach
报 告 人：Haixun Wang (王海勋), 微软亚洲研究院
报告时间：2009 年 12 月 29 日上午10:00–11:30
Haixun Wang recently joined Microsoft Research Asia in Beijing, China. Before joining Microsoft, he was a research staff member at IBM T. J. Watson Research Center. He had been a Technical Assistant to Stuart Feldman, Vice President of Computer Science of IBM Research, from 2006 to 2007, and Technical Assistant to Mark Wegman, Head of Computer Science of IBM Research from 2007 to 2009. He received the B.S. and the M.S. degree, both in computer science, from Shanghai Jiao Tong University in 1994 and 1996. He received the Ph.D. degree in computer science from the University of California, Los Angeles in 2000. His main research interest is database language and systems, data mining, and information retrieval. He has published more than 100 research papers in referred international journals and conference proceedings. He is an association editor of TKDE, and he was PC Vice Chair of KDD'10, ICDM’09, SDM’08, KDD’08, Demo PC Chair of ICDE’09 and ICDM’08, Sponsor Chair of SIGMOD’08, etc., and he serves in program committees of various international conferences and workshops in the database field, including the coming SIGMOD'10 and VLDB'10.
Cloud computing has potential to revolutionize the IT industry as it enables clients to focus on application design rather than the scalability and availability of the underlying database and hardware. Data storage is the core component of all cloud-based solutions. A fundamental challenge in data storage design for the cloud environment is how to trade off scalability/availability with data consistency. Currently, most cloud-based architectures opted to strip down data management to its bare essentials, and many of them implement a simple, ad-hoc storage model such as the key/value storage model to maximize scalability. We argue that since the eventual goal of cloud computing is to better serve a large variety of applications, the need for advanced data management will certainly persist, and matured cloud-based architectures will have to satisfy this need. Instead of becoming obsolete, relational DBMS and relational theory are a perfect candidate for this task. Furthermore, leveraging DBMS also allows the benefits of cloud computing to be extended to the existing DBMS based Web applications. We propose a data consistency model for the cloud environment, and we show that it can be implemented on top of current relational DBMS without modifying the database engine. Our solution is able to achieve high concurrency and high availability for data management need in cloud computing.