Subquery allocations in distributed databases using genetic algorithms

Minimization of query execution time is an important performance objective in distributed databases design. While total time is to be minimized for On Line Transaction Processing (OLTP) type queries, response time has to be minimized in Decision Support type queries. Thus different allocations of su...

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Detalles Bibliográficos
Autores principales: Gorla, Narasimhaiah, Song, Suk-Kyu
Formato: Articulo
Lenguaje:Inglés
Publicado: 2010
Materias:
Ciencias Informáticas
Distributed databases
response time minimization
physical database design
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/9665
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr10-6.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-9665
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Distributed databases
response time minimization
physical database design
spellingShingle Ciencias Informáticas
Distributed databases
response time minimization
physical database design
Gorla, Narasimhaiah
Song, Suk-Kyu
Subquery allocations in distributed databases using genetic algorithms
topic_facet Ciencias Informáticas
Distributed databases
response time minimization
physical database design
description Minimization of query execution time is an important performance objective in distributed databases design. While total time is to be minimized for On Line Transaction Processing (OLTP) type queries, response time has to be minimized in Decision Support type queries. Thus different allocations of subqueries to sites and their execution plans are optimal based on the query type. We formulate the subquery allocation problem and provide analytical cost models for these two objective functions. Since the problem is NP-hard, we solve the problem using genetic algorithm (GA). Our results indicate query execution plans with total minimization objective are inefficient for response time objective and vice versa. The GA procedure is tested with simulation experiments using complex queries of up to 20 joins. Comparison of results with exhaustive enumeration indicates that GA produced optimal solutions in all cases in much less time.
format Articulo
Articulo
author Gorla, Narasimhaiah
Song, Suk-Kyu
author_facet Gorla, Narasimhaiah
Song, Suk-Kyu
author_sort Gorla, Narasimhaiah
title Subquery allocations in distributed databases using genetic algorithms
title_short Subquery allocations in distributed databases using genetic algorithms
title_full Subquery allocations in distributed databases using genetic algorithms
title_fullStr Subquery allocations in distributed databases using genetic algorithms
title_full_unstemmed Subquery allocations in distributed databases using genetic algorithms
title_sort subquery allocations in distributed databases using genetic algorithms
publishDate 2010
url http://sedici.unlp.edu.ar/handle/10915/9665
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr10-6.pdf
work_keys_str_mv AT gorlanarasimhaiah subqueryallocationsindistributeddatabasesusinggeneticalgorithms
AT songsukkyu subqueryallocationsindistributeddatabasesusinggeneticalgorithms
bdutipo_str Repositorios
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