An adaptive parallel query processing middleware for the Grid: Research Articles

Authors:
V. F. V. Da Silva;M. L. Dutra;F. Porto;B. Schulze;A. C. Barbosa;J. C. de Oliveira
Affiliations:
Computer Science Department, National Laboratory for Scientific Computation, Rio de Janeiro, Brazil and Informatics Department, Pontificial Catholic University, Rio de Janeiro, Brazil;Computer Science Department, National Laboratory for Scientific Computation, Rio de Janeiro, Brazil and System Engineering Department, Military Institute of Engineering, Rio de Janeiro, Brazil;EPFL, School of Computer and Communication Sciences, Database Laboratory, Lausanne, Switzerland;Computer Science Department, National Laboratory for Scientific Computation, Rio de Janeiro, Brazil;Computer Science Department, Federal University of Espírito Santo, Espírito Santo, Brazil;Computer Science Department, National Laboratory for Scientific Computation, Rio de Janeiro, Brazil
Venue:
Concurrency and Computation: Practice & Experience - Middleware for Grid Computing
Year:
2006

Citing 0
Cited 3

Evolution of Query Optimization Methods: From Centralized Database Systems to Data Grid Systems

DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
Resource scheduling methods for query optimization in data grid systems

ADBIS'11 Proceedings of the 15th international conference on Advances in databases and information systems
Resource allocation algorithm for a relational join operator in grid systems

Proceedings of the 16th International Database Engineering & Applications Sysmposium

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.