vices provide an important abstract layer on top of heterogeneous components (hardware and software) that take part into a grid environment. In this scenario, applications, like scientific visualization, require access to data of non-conventional data types, like fluid path geometry, and the evaluation of special user programs and algebraic operators, like spatial hash-join, on these data. In order to support such applications we are developing CoDIMS-G, which is an adaptive parallel query processing middleware for the grid. 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 scheduled node and nicely deals with repetitive evaluation of a query execution plan fragment, as needed for computing particles trajectory. key words: Middleware; Grid Services; Database; Parallel Query Processing
Vinícius F. V. da Silva, Márcio L. D