Efficient Algorithms to Monitor Continuous Constrained k Nearest Neighbor Queries

  • Mahady Hasan
  • Muhammad Aamir Cheema
  • Wenyu Qu
  • Xuemin Lin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5981)


Continuous monitoring of spatial queries has received significant research attention in the past few years. In this paper, we propose two efficient algorithms for the continuous monitoring of the constrained k nearest neighbor (kNN) queries. In contrast to the conventional k nearest neighbors (kNN) queries, a constrained kNN query considers only the objects that lie within a region specified by some user defined constraints (e.g., a polygon). Similar to the previous works, we also use grid-based data structure and propose two novel grid access methods. Our proposed algorithms are based on these access methods and guarantee that the number of cells that are accessed to compute the constrained kNNs is minimal. Extensive experiments demonstrate that our algorithms are several times faster than the previous algorithm and use considerably less memory.


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  1. 1.
    Mouratidis, K., Hadjieleftheriou, M., Papadias, D.: Conceptual partitioning: An efficient method for continuous nearest neighbor monitoring. In: SIGMOD Conference, pp. 634–645 (2005)Google Scholar
  2. 2.
    Yu, X., Pu, K.Q., Koudas, N.: Monitoring k-nearest neighbor queries over moving objects. In: ICDE, pp. 631–642 (2005)Google Scholar
  3. 3.
    Xiong, X., Mokbel, M.F., Aref, W.G.: Sea-cnn: Scalable processing of continuous k-nearest neighbor queries in spatio-temporal databases. In: ICDE, pp. 643–654 (2005)Google Scholar
  4. 4.
    Cheema, M.A., Brankovic, L., Lin, X., Zhang, W., Wang, W.: Multi-guarded safe zone: An effective technique to monitor moving circular range queries. To appear in ICDE (2010)Google Scholar
  5. 5.
    Xia, T., Zhang, D.: Continuous reverse nearest neighbor monitoring. In: ICDE, p. 77 (2006)Google Scholar
  6. 6.
    Cheema, M.A., Lin, X., Zhang, Y., Wang, W., Zhang, W.: Lazy updates: An efficient technique to continuously monitoring reverse knn. VLDB 2(1), 1138–1149 (2009)Google Scholar
  7. 7.
    Ferhatosmanoglu, H., Stanoi, I., Agrawal, D., Abbadi, A.E.: Constrained nearest neighbor queries. In: SSTD, pp. 257–278 (2001)Google Scholar
  8. 8.
    Wu, W., Yang, F., Chan, C.Y., Tan, K.L.: Continuous reverse k-nearest-neighbor monitoring. In: MDM, pp. 132–139 (2008)Google Scholar
  9. 9.
    Guttman, A.: R-trees: A dynamic index structure for spatial searching. In: SIGMOD Conference, pp. 47–57 (1984)Google Scholar
  10. 10.
    Hjaltason, G.R., Samet, H.: Ranking in spatial databases. In: SSD, pp. 83–95 (1995)Google Scholar
  11. 11.
    Gao, Y., Chen, G., Li, Q., Li, C., Chen, C.: Constrained k-nearest neighbor query processing over moving object trajectories. In: Haritsa, J.R., Kotagiri, R., Pudi, V. (eds.) DASFAA 2008. LNCS, vol. 4947, pp. 635–643. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  12. 12.
    Mokbel, M.F., Xiong, X., Aref, W.G.: Sina: Scalable incremental processing of continuous queries in spatio-temporal databases. In: SIGMOD Conference, pp. 623–634 (2004)Google Scholar
  13. 13.
    Zhang, J., Zhu, M., Papadias, D., Tao, Y., Lee, D.L.: Location-based spatial queries. In: SIGMOD Conference, pp. 443–454 (2003)Google Scholar
  14. 14.
    Wu, W., Tan, K.L.: isee: Efficient continuous k-nearest-neighbor monitoring over moving objects. In: SSDBM, p. 36 (2007)Google Scholar
  15. 15.
    Cheema, M.A.: Circulartrip and arctrip: effective grid access methods for continuous spatial queries. UNSW Masters Thesis (2007), http://handle.unsw.edu.au/1959.4/40512
  16. 16.
    Cheema, M.A., Yuan, Y., Lin, X.: Circulartrip: An effective algorithm for continuous nn queries. In: Kotagiri, R., Radha Krishna, P., Mohania, M., Nantajeewarawat, E. (eds.) DASFAA 2007. LNCS, vol. 4443, pp. 863–869. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  17. 17.
    Brinkhoff, T.: A framework for generating network-based moving objects. GeoInformatica 6(2), 153–180 (2002)MATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Mahady Hasan
    • 1
  • Muhammad Aamir Cheema
    • 1
  • Wenyu Qu
    • 2
  • Xuemin Lin
    • 1
  1. 1.The University of New South WalesAustralia
  2. 2.College of Information Science and TechnologyDalian Maritime UniversityChina

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