A Cost Model for an Adaptive Cell-Based Index Structure

摘要

In this paper, we describe a cost model for an adaptive cell-based index structure which aims at efficient management of immense amounts of spatio-temporal data. We first survey various methods to estimate the performance of R-tree variants. Then, we present our cost model which accurately estimates the number of disk accesses for the adaptive cell-based index structure. To show the accuracy of our model, we perform a detailed analysis using various data sets. The experimental result shows that our model has the average error ratio from 7% to 13%.