Title
GreenDB: Energy-efficient prefetching and caching in database clusters
Document Type
Article
Publication Date
5-1-2019
Publication Title
IEEE Transactions on Parallel and Distributed Systems
Volume
30
First Page
1091
Last Page
1104
Keywords
energy conservation, Energy efficiency, prefetching
Abstract
© 1990-2012 IEEE. In this study, we propose an energy-efficient database system called GreenDB running on clusters. GreenDB applies a workload-skewness strategy by managing hot nodes coupled with a set of cold nodes in a database cluster. GreenDB fetches popular data tables to hot nodes, aiming to keep cold nodes in the low-power mode in increased time periods. GreenDB is conducive to reducing the number of power-state transitions, thereby lowering energy-saving overhead. A prefetching model and an energy saving model are seamlessly integrated into GreenDB to facilitate the power management in database clusters. We quantitatively evaluate GreenDB's energy efficiency in terms of managing, fetching, and storing data. We compare GreenDB's prefetching strategy with the one implemented in Postgresql. Experimental results indicate that GreenDB conserves the energy consumption of the existing solution by up to 98.4 percent. The findings show that the energy efficiency of GreenDB can be optimized by tuning system parameters, including table size, hit rates, number of nodes, number of disks, and inter-arrival delays.
Recommended Citation
Zhou, Yi; Taneja, Shubbhi; Zhang, Chaowei; and Qin, Xiao, "GreenDB: Energy-efficient prefetching and caching in database clusters" (2019). Faculty Bibliography. 2779.
https://csuepress.columbusstate.edu/bibliography_faculty/2779