Effective Data Localization Using Consistent Hashing in Cloud Time-Series Databases

摘要：

　　The commercial time-series database is suitable for processing the time-series data.However,a single commercial time-series database can only accommodate the time-series data acquired by limited amount of sensors.In this paper,in order to cope with the challenge of massive time-series data processing,we first propose a cloud time-series database framework based on commercial time-series databases,and then propose an effective consistent hashing based algorithm for solving the key problem,i.e.,the data localization problem,in cloud time-series databases.A performance study shows the superiority of the framework and the algorithm for processing massive time-series data acquired by large amount of sensors.

关键词： time-series data massive data data localization consistent hashing time-series database cloud database sensor

作者: Jiakui Zhao Pingfei Zhu Liang Huai Yang

作者单位: Beijing China-Power Information Technology Co.,Ltd.State Grid Electric Power Research Institute Beij School of Computer Science and Technology Zhejiang University of Technology Hangzhou,China

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Computer Science and Electronics Engineering(ICCSEE2013)(2013年第二届计算机科学与电子工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 2425-2428

在线出版日期: 2013-03-22（万方平台首次上网日期，不代表论文的发表时间）