Abstract
In multimedia databases, the spatial index structures based on trees (like R-tree, M-tree) have been proved to be efficient and scalable for low-dimensional data retrieval. However, if the data dimensionality is too high, the hierarchy of nested regions (represented by the tree nodes) becomes spatially indistinct.
Hence, the query processing deteriorates to inefficient index traversal (in terms of random-access I/O costs) and in such case the tree-based indexes are less efficient than the sequential search. This is mainly due to repeated access to many nodes at the top levels of the tree.
In this paper we propose a modified storage layout of tree-based indexes, such that nodes belonging to the same tree level are stored together. Such a level-ordered storage allows to prefetch several top levels of the tree into the buffer pool by only a few or even a single contiguous I/O operation (i.e. one-seek read).
The experimental results show that our approach can speedup the tree-based search significantly.