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

DOI

10.2991/iccsee.2013.607How to use a DOI?

Keywords

time-series data, massive data, data localization, consistent hashing, time-series database, cloud database, sensor.

Abstract

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jiakui Zhao
AU  - Pingfei Zhu
AU  - Liang Huai Yang
PY  - 2013/03
DA  - 2013/03
TI  - Effective Data Localization Using Consistent Hashing in Cloud Time-Series Databases
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 2424
EP  - 2427
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.607
DO  - 10.2991/iccsee.2013.607
ID  - Zhao2013/03
ER  -