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Adaptive Indexing of Moving Objects with Highly Variable Update Frequencies

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Abstract

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 Bx-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 By-tree and αBy-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 αBy-tree can balance the performance of updates and queries depending on a balance parameter. Experimental results show that the By-tree and αBy-tree outperform the Bx-tree in various conditions.

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References

  1. Christian S Jensen, Dalia Tiesyte, Nerius Tradisauskas. Robust B+-tree-based indexing of moving objects. In Proc. MDM, Nara, Japan, 2006, p.12.

  2. Antonin Guttman. R-trees: A dynamic index structure for spatial searching. In Proc. SIGMOD Conference, Boston, MA, USA, 1984, pp.47–57.

  3. Simonas Saltenis, Christian S Jensen, Scott T Leutenegger, Mario A Lopez. Indexing the positions of continuously moving objects. In Proc. SIGMOD Conference, Dallas, TX, USA, 2000, pp.331–342.

  4. Simonas Saltenis, Christian S Jensen. Indexing of moving objects for location-based services. In Proc. ICDE, San Jose, CA, USA, 2002, pp.463–472.

  5. Yufei Tao, Dimitris Papadias, Jimeng Sun. The TPR*-tree: An optimized spatio-temporal access method for predictive queries. In Proc. VLDB, Berlin, Germany, 2003, pp.790–801.

  6. Jignesh M Patel, Yun Chen, V Prasad Chakka. STRIPES: An efficient index for predicted trajectories. In Proc. SIGMOD Conference, Paris, France, 2004, pp.637–646.

  7. Hanan Samet. The quadtree and related hierarchical data structures. ACM Comput. Surv., 1984, 16(2): 187–260.

    Article  MathSciNet  Google Scholar 

  8. Christian S Jensen, Dan Lin, Beng Chin Ooi. Query and update efficient B+-tree based indexing of moving objects. In Proc. VLDB, Toronto, Ontario, Canada, 2004, pp.768–779.

  9. Mohamed F Mokbel, Thanaa M Ghanem, Walid G Aref. Spatio-temporal access methods. IEEE Data Eng. Bull., 2003, 26(2): 40–49.

    Google Scholar 

  10. Bin Lin, Hoda Mokhtar, Rafael Pelaez-Aguilera, Jianwen Su. Querying moving objects with uncertainty. In Proc. Vehicular Technology Conference, Orlando, FL, USA, 2003, pp.2783–2787.

  11. Ji-Dong Chen, Xiao-Feng Meng. Indexing future trajectories of moving objects in a constrained network. Journal of Computer Science and Technology, 2007, 22(2): 245–251.

    Article  Google Scholar 

  12. Yufei Tao, Jun Zhang, Dimitris Papadias, Nikos Mamoulis. An efficient cost model for optimization of nearest neighbor search in low and medium dimensional spaces. IEEE Trans. Knowl. Data Eng., 2004, 16(10): 1169–1184.

    Article  Google Scholar 

  13. Mong-Li Lee, Wynne Hsu, Christian S. Jensen, Bin Cui, Keng Lik Teo. Supporting frequent updates in R-trees: A bottom-up approach. In Proc. VLDB, Berlin, Germany, 2003, pp.608–619.

  14. Xiaopeng Xiong, Walid G Aref. R-trees with update memos. In Proc. ICDE, Atlanta, Georgia, USA, 2006, p.22.

  15. Goetz Graefe. B-tree indexes for high update rates. SIGMOD Record, 2006, 35(1): 39–44.

    Article  Google Scholar 

  16. Bongki Moon, H V Jagadish, Christos Faloutsos, Joel H Saltz. Analysis of the clustering properties of the Hilbert space-filling curve. IEEE Trans. Knowl. Data Eng., 2001, 13(1): 124–141.

    Article  Google Scholar 

  17. V Srinivasan, Michael J Carey. Performance of B-tree concurrency algorithms. In Proc. SIGMOD Conference, Denver, CO, USA, 1991, pp.416–425.

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Authors and Affiliations

  1. College of Computer Science, Zhejiang University, Hangzhou, 310027, China

    Nan Chen, Li-Dan Shou, Gang Chen & Jin-Xiang Dong

Authors
  1. Nan Chen
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  2. Li-Dan Shou
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  3. Gang Chen
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  4. Jin-Xiang Dong
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Corresponding author

Correspondence to Li-Dan Shou.

Additional information

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).

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Chen, N., Shou, LD., Chen, G. et al. Adaptive Indexing of Moving Objects with Highly Variable Update Frequencies. J. Comput. Sci. Technol. 23, 998–1014 (2008). https://doi.org/10.1007/s11390-008-9185-0

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  • DOI: https://doi.org/10.1007/s11390-008-9185-0

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