A New Approach for Optimization of Dynamic Metric Access Methods Using an Algorithm of Effective Deletion

Abstract

The existing Metric Access Methods (MAM) assume the data elements represent immutable objects. However, many applications must handle complex data evolving over time. Health care, weather monitoring, and other applications require removing or updating elements. Most of the MAM presented in the literature either do not have the deletion operation described, or it is performed just marking the element as deleted without effectively removing it from the structure. In this paper we describe an algorithm that effectively removes any element from a metric tree. While maintaining the height-balancing of the structure, the proposed deletion algorithm uses mechanisms to enforce a reduced number of pages in the tree, improving the query performance. Based on the deletion algorithm, we propose a new way to optimize a MAM, which we call the Push-pull technique. It reduces the node overlap performing the deletion and reinsertion of elements close to the border of each node covering region. We also developed the Smart Push-pull algorithm, which uses statistical data about subtrees’ overlapping to calculate how many elements should be removed from each node. The statistics are collected during the evaluation of the structure overlap, an operation employed to ascertain the need to trigger an optimization process. The experiments were run on the Slim-tree and showed a reduction of overlap and a query performance improvement over trees optimized by this technique as compared over trees optimized by the Slim-down method.