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Adaptive Indexing of Moving Objects with Highly Variable Update Frequencies

Nan Chen, Li-Dan Shou*, Gang Chen, and Jin-Xiang Dong   

  1. College of Computer Science, Zhejiang University, Hangzhou 310027, China
  • Received:2007-06-27 Revised:2008-05-13 Online:2008-11-10 Published:2008-11-10

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 $\al {\rm B}^y$-tree. By associating a {\em prediction life period} with every moving object, the proposed indexes are applicable in the environments with highly variable update frequencies. In addition, the $\al {\rm B}^y$-tree can balance the performance of updates and queries depending on a balance parameter. Experimental results show that the B$^y$-tree and $\al {\rm B}^y$-tree outperform the B$^x$-tree in various conditions.

Key words: deductive language; embroidery pattern; operators of space relation;


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