Abstract
The emergence of computational grids, as global computing infrastructures, calls for development of new and advanced database techniques. While there exist algorithms and tools that facilitate database operations in grids, currently query optimization techniques are scant. In this paper, a query optimization technique, Grid Query Optimizer (GQO), that improves overall response time for grid-based query processing is presented. GQO features a resource selection strategy and a generic parallelism processing algorithm to balance optimization cost and query execution. GQO is tested using a simulated grid environment and compared with two other optimization techniques. Experiment results show that GQO provides better-than-average performance and is especially suitable for queries with large search spaces.
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