Particle swarm optimisation for data warehouse logical design

被引：8

作者：

Derrar, Hacene ^{[1
]}

Ahmed-Nacer, Mohamed ^{[1
]}

Boussaid, Omar ^{[2
]}

机构：

[1] Univ Sci & Technol Houari Boumediene, Fac Elect & Comp Sci, LSI Lab, Algiers, Algeria

[2] Univ Lyon 2, ERIC Lab, F-69676 Bron, France

来源：

INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION | 2012年 / 4卷 / 04期

关键词：

data warehouse; OLAP queries; fragmentation; performance; particle swarm optimisation; PSO; bio-inspired computation; GENETIC ALGORITHM; FRAGMENTATION;

D O I：

10.1504/IJBIC.2012.048072

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Data fragmentation is one of the physical database design techniques that improves significantly data management, accessibility and query execution time. Optimal fragmentation schema is designed from workload gathered from data exploitation. However, adapting this technique to data warehouse should consider the specific characteristics of data warehouse such as the complexity of OLAP queries and the dynamicity of data model and workload. In this paper, data fragmentation is formalised as an optimisation problem with constraint and we propose the application of particle swarm optimisation (PSO) technique to design an optimal fragmentation schema.

引用

页码：249 / 257

页数：9

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