Quality-aware Scheduling for Key-value Data Stores

Introduction. - Literature and Research Review. - Problem Overview. - Scheduling for State-Transfer Updates. - Scheduling for Operation-Transfer Updates. - AQUAS: A Quality-Aware Scheduler. - Conclusion and Future Work.

Chen Xu received his PhD degree from East China Normal University (ECNU) in 2014 and Bachelor degree from Hefei University of Technology (HFUT) in 2009. In 2011, Chen studied as visiting student at The University of Queensland (UQ) supported by a research fellowship from UQ. He held the honors of outstanding graduates from ECNU and HFUT as well as Anhui provincial government of P.R. China. He was the winner of the National Scholarship from Ministry of Education of P.R. China in 2008. Chen has publications in academic journal such as Distributed and Parallel Databases (DAPD), and conferences including ICDE, DASFAA, etc. He is serving as a reviewer of Frontier of Computer Science (FCS). His research interest includes data management for data-intensive computing, large-scale data analysis, etc. Aoying Zhou is a professor on Computer Science at East China Normal University (ECNU), where he is heading the Institute for Data Science and Engineering. He got his master and bachelor degree in Computer Science from Sichuan University, in 1988 and 1985 respectively, and he won his Ph.D. degree from Fudan University in 1993. Before joining ECNU in 2008, Aoying worked for Fudan University at the Computer Science Department for 15 years. He is the winner of the National Science Fund for Distinguished Young Scholars supported by NSFC and the professorship appointment under Changjiang Scholars Program of Ministry of Education in China. He is now acting as a vice-director of ACM SIGMOD China and Database Technology Committee of China Computer Federation. He is serving as a member of the editorial boards VLDB Journal, WWW Journal, and etc. His research interests include Web data management, data management for data-intensive computing, memory cluster computing, benchmarking for big data and performance.