Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/72060
Título: | Life inspired algorithms for the selection of OLAP data cubes |
Autor(es): | Loureiro, Jorge Belo, Orlando |
Palavras-chave: | Genetic and particle swarm algorithms On-line analytical processing Cube views selection |
Data: | Jan-2006 |
Editora: | World Scientific and Engineering Academy and Society (WSEAS) |
Revista: | WSEAS Transactions on Computers |
Resumo(s): | The use of materialized views is a common technique to speed up on-line analytical processing. However, the huge amount of data usually stored in data warehouses, and the complexity of their schemas, implies that only a few of the total aggregated views may be materialized. The correct selection of the materialized views is a basic condition for performance, but it is a recognized NP-hard problem. Several heuristics were proposed to the design of specific algorithms to solve that problem, being the most relevant the greedy and evolutionary ones, In this paper, we study the performance of two biological inspired algorithms applied to the cube selection problem: a genetic and a discrete particle swarm - both algorithms consider query and maintenance costs and space constraints. According to the experimental results carried on, both algorithms showed a speed of execution, convergence capacity, and consistence that allow electing them to use in data warehoust systems of medium and moderated size, being the swarm solution the one with better overall performance. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/72060 |
ISSN: | 1109-2750 |
e-ISSN: | 2224-2872 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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2006-JN-ISCOCO-Loureiro&Belo-CRP.pdf Acesso restrito! | 234,1 kB | Adobe PDF | Ver/Abrir |