Efficient Querying Of Trajectory Data In Relational Database

This paper focuses on efficiently processing trajectory-based queries for spatio-temporal data. Emphasis of using B-tree as the index method is proposed. Three ways to structure and query data are introduced. EDBS which scan all data set is a naive idea and servers as the baseline. Another idea RSTI utilizes B-tree indices in each dimension to realize the range selection. DTI takes advantage of Hilbert Curve and grid cells methods to transfer the multi-dimensional data to one dimensional data and use RI-Tree in time interval. The performance comparison among the given methods is given through the experiments part, and pick the most efficient structure to compare with R-Tree which is a method special for multi-dimensional method, the gap between them is not significant..