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An adaptive parallel query processing middleware for the Grid
Author(s) -
Da Silva V. F. V.,
Dutra M. L.,
Porto F.,
Schulze B.,
Barbosa A. C.,
de Oliveira J. C.
Publication year - 2006
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.970
Subject(s) - computer science , grid computing , grid , distributed computing , query plan , scheduling (production processes) , middleware (distributed applications) , software , query optimization , visualization , database , data mining , operating system , web search query , sargable , information retrieval , search engine , operations management , geometry , mathematics , economics
Grid services provide an important abstract layer on top of heterogeneous components (hardware and software) that take part in a Grid environment. In this scenario, applications such as scientific visualization require access to data of non‐conventional data types, such as fluid path geometry, and the evaluation of special user programs and algebraic operators, such as spatial hash‐join, on these data. In order to support such applications we are developing a Configurable Data Integration Middleware System for the Grid (CoDIMS‐G). CoDIMS‐G provides a query execution environment adapted to the heterogeneity and variations found in a Grid environment by offering a node scheduling algorithm and an adaptive query execution strategy. The latter both adapts to performance variations in a scheduled node and deals efficiently with repetitive evaluation of a query execution plan fragment, as needed for computing a particle's, trajectory. Copyright © 2005 John Wiley & Sons, Ltd.