Sorting AR*-tree: Further improving the performance of partially-dimensional range queries

It is well known that multidimensional indices are helpful to improve the performance of range queries in multi-dimensional spaces. An n-dimensional index is often used for evaluating n-dimensional queries. However in many applications using range queries, the query dimensions of each range query are likely of only part (rather than all) of the index dimensions]. Such range queries are referred to as partially-dimensional (PD) range queries in our previous study [1]. That is, although the index is built in an n-dimensional space, the actual range queries may only use d dimensions of the n dimensional index space (d < n). If the existing multidimensional indices are employed to evaluate PD range queries, then a great deal of information that is irrelevant to the queries also has to be read from disk. In order to solve this problem, we proposed a modification of R*-tree, called Adaptive R*-tree (AR*-tree). This paper is about how to further improve the search performance of the AR*-tree for PD range queries by sorting the entries in AR*-tree nodes.