Adaptive Indexing of Moving Objects with Highly Variable Update Frequencies

In recent years, management of moving objects has emerged as an active topic of spatial access methods. Various data structures (indexes) have been proposed to handle queries of moving points, for example, the well-known B x -tree uses a novel mapping mechanism to reduce the index update costs. However, almost all the existing indexes for predictive queries are not applicable in certain circumstances when the update frequencies of moving objects become highly variable and when the system needs to balance the performance of updates and queries. In this paper, we introduce two kinds of novel indexes, named B y -tree and αB y -tree. By associating a prediction life period with every moving object, the proposed indexes are applicable in the environments with highly variable update frequencies. In addition, the αB y -tree can balance the performance of updates and queries depending on a balance parameter. Experimental results show that the B y -tree and αB y -tree outperform the B x -tree in various conditions. Electronic supplementary material The online version of this article (doi: ) contains supplementary material, which is available to authorized users. This work is supported in part by Program for Changjiang Scholars and Innovative Research Team in University (Grant No. IRT0652), and the National Natural Science Foundation of China (Grant No. 60603044).