Optimization of Disk Accesses for Multidimensional Range Queries

Multidimensional data structures have become very popular in recent years. Their importance lies in efficient indexing of data, which have naturally multidimensional characteristics like navigation data, drawing specifications etc. The R-tree is a well-known structure based on the bounding of spatial near points by rectangles. Although efficient query processing of multidimensional data is requested, the R-tree has been shown to be inefficient in many cases. From the disk access cost point of view, the main issue of range query processing is the expensive cost of random accesses during the tree traversal. In the case of queries with low selectivity, the sequential scan of all tuples may be more efficient than the range query processing. We focus on efficiency of the disk access cost and we present an optimization of the disk access cost during range query processing. Our method focuses on a leaf node retrieval and it can be simply adopted by any tree. We put forward our tests using the R-tree since it is the most common multidimensional data structure.