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Journal of Zhejiang University SCIENCE A 2006 Vol.7 No.10 P.1642~1651

http://doi.org/10.1631/jzus.2006.A1642


Automatic relational database compression scheme design based on swarm evolution


Author(s):  HU Tian-lei, CHEN Gang, LI Xiao-yan, DONG Jin-xiang

Affiliation(s):  School of Computer Science and technology, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   andy_hu@263.net

Key Words:  Database compression, Automatic physical database design, Swarm evolution


HU Tian-lei, CHEN Gang, LI Xiao-yan, DONG Jin-xiang. Automatic relational database compression scheme design based on swarm evolution[J]. Journal of Zhejiang University Science A, 2006, 7(10): 1642~1651.

@article{title="Automatic relational database compression scheme design based on swarm evolution",
author="HU Tian-lei, CHEN Gang, LI Xiao-yan, DONG Jin-xiang",
journal="Journal of Zhejiang University Science A",
volume="7",
number="10",
pages="1642~1651",
year="2006",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A1642"
}

%0 Journal Article
%T Automatic relational database compression scheme design based on swarm evolution
%A HU Tian-lei
%A CHEN Gang
%A LI Xiao-yan
%A DONG Jin-xiang
%J Journal of Zhejiang University SCIENCE A
%V 7
%N 10
%P 1642~1651
%@ 1673-565X
%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.A1642

TY - JOUR
T1 - Automatic relational database compression scheme design based on swarm evolution
A1 - HU Tian-lei
A1 - CHEN Gang
A1 - LI Xiao-yan
A1 - DONG Jin-xiang
J0 - Journal of Zhejiang University Science A
VL - 7
IS - 10
SP - 1642
EP - 1651
%@ 1673-565X
Y1 - 2006
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2006.A1642


Abstract: 
Compression is an intuitive way to boost the performance of a database system. However, compared with other physical database design techniques, compression consumes large amount of CPU power. There is a trade-off between the reduction of disk access and the overhead of CPU processing. Automatic design and adaptive administration of database systems are widely demanded, and the automatic selection of compression schema to compromise the trade-off is very important. In this paper, we present a model with novel techniques to integrate a rapidly convergent agent-based evolution framework, i.e. the SWAF (SWarm Algorithm Framework), into adaptive attribute compression for relational database. The model evolutionally consults statistics of CPU load and IO bandwidth to select compression schemas considering both aspects of the trade-off. We have implemented a prototype model on Oscar RDBMS with experiments highlighting the correctness and efficiency of our techniques.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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