다양한 이동 객체 궤적의 효율적 분할 방법에 관한 연구

Abstract

Recently, use of various position base service that collect position information for moving object and utilize in real life is increasing by the development of wireless network technology. Moving-objects databases should efficiently support database queries that refer to the trajectories and positions of continuously moving objects. To improve the performance of these queries, an efficient indexing scheme for continuously moving objects is required. Moving object means spatio-temporal data that change space location consecutively by time change. Method to create index be to using MBR as an approximation to the actual data area. We focused on efficiently splitting MBR for the searching for trajectory of moving object. In method to search trajectory-based data, splitting trajectory for processing space query is very important. However, on such spatio-temporal trajectory, the trajectory's points are myriad. Storing and searching all information of these trajectories is time-consuming and it is inefficient. Also, if it is long distance of location of trajectory between point and point. it bring very much dead space and false drop. In this dissertation, we propose the Improved Split Algorithm that splits the search space efficiently. and the k-split Algorithm on restricted storage space and the Estimated Split Algorithm that splits optimally long distance between point and point in single trajectory and finally Total Estimated Algorithm that split efficiently various moving object trajectories. We have designed and simulated each algorithm. Our experimental evaluation confirms the effectiveness and efficiency of our proposed splitting policy.