Quadtree and Hash Table Based Index Structure for Indexing the Past, Present and Future Positions of Moving Objects

Traditional index structures do not work well on moving objects because of the need of frequently updating the index which leads to the poor performance. This paper presents a novel index structure based on the improved Quadtree and Hash table, namely the QH-index which can index the past, present and future positions of moving objects and can support moving objects´ range queries and point queries that include the object identifier based query. Merging timely the corresponding nodes to degrade the depth of the tree can guarantee the query efficiency. Our experiments show that the QH-index gains much better performance in updating and in querying by the object identifier than those of the TPR-tree, and the efficiency of range query is no less than that of TPR-tree.