Abstract
AbstractGrid 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.
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