Skip to main content
SpringerLink
Log in

Continuous visible nearest neighbor query processing in spatial databases

  • Regular Paper
  • Published:
The VLDB Journal Aims and scope Submit manuscript

Abstract

In this paper, we identify and solve a new type of spatial queries, called continuous visible nearest neighbor (CVNN) search. Given a data set P, an obstacle set O, and a query line segment q in a two-dimensional space, a CVNN query returns a set of \({\langle p, R\rangle}\) tuples such that \({p \in P}\) is the nearest neighbor to every point r along the interval \({R \subseteq q}\) as well as p is visible to r. Note that p may be NULL, meaning that all points in P are invisible to all points in R due to the obstruction of some obstacles in O. In contrast to existing continuous nearest neighbor query, CVNN retrieval considers the impact of obstacles on visibility between objects, which is ignored by most of spatial queries. We formulate the problem, analyze its unique characteristics, and develop efficient algorithms for exact CVNN query processing. Our methods (1) utilize conventional data-partitioning indices (e.g., R-trees) on both P and O, (2) tackle the CVNN search by performing a single query for the entire query line segment, and (3) only access the data points and obstacles relevant to the final query result by employing a suite of effective pruning heuristics. In addition, several interesting variations of CVNN queries have been introduced, and they can be supported by our techniques, which further demonstrates the flexibility of the proposed algorithms. A comprehensive experimental evaluation using both real and synthetic data sets has been conducted to verify the effectiveness of our proposed pruning heuristics and the performance of our proposed algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Song, Z., Roussopoulos, N.: K-nearest neighbor search for moving query point. In: SSTD, pp. 79–96 (2001)

  2. Tao, Y., Papadias, D.: Time parameterized queries in spatio- temporal databases. In: SIGMOD, pp. 334–345 (2002)

  3. Tao, Y., Papadias, D., Shen, Q.: Continuous nearest neighbor search. In: VLDB, pp. 287–298 (2002)

  4. Nutanong, S., Tanin, E., Zhang, R.: Visible nearest neighbor queries. In: DASFAA, pp. 876–883 (2007)

  5. Nutanong S., Tanin E., Zhang R.: Incremental evaluation of visible nearest neighbor queries. IEEE Trans. Knowl. Data Eng. 22(5), 665–681 (2010)

    Article  Google Scholar 

  6. Gao, Y., Zheng, B., Chen, G., Lee, W.C., Lee, K.C.K., Li, Q.: Visible reverse k-nearest neighbor queries. In: ICDE, pp. 1203–1206 (2009)

  7. Gao Y., Zheng B., Chen G., Lee W.C., Lee K.C.K., Li Q.: Visible reverse k-nearest neighbor query processing in spatial databases. IEEE Trans. Knowl. Data Eng. 21(9), 1314–1327 (2009)

    Article  Google Scholar 

  8. Xia, C., Hsu, D., Tung, A.K.H.: A fast filter for obstructed nearest neighbor queries. In: BNCOD, pp. 203–215 (2004)

  9. Zhang, J., Papadias, D., Mouratidis, K., Zhu, M.: Spatial queries in the presence of obstacles. In: EDBT, pp. 366–384 (2004)

  10. Gao, Y., Zheng, B.: Continuous obstructed nearest neighbor queries in spatial databases. In: SIGMOD, pp. 577–590 (2009)

  11. Estivill-Castro, V., Lee, I.: Autoclust+: Automatic clustering of point-data sets in the presence of obstacles. In: TSDM, pp. 133–146 (2000)

  12. Park, S.H., Lee, J.H., Kim, D.H.: Spatial clustering based on moving distance in the presence of obstacles. In: DASFAA, pp. 1024–1027 (2007)

  13. Tung, A.K.H., Hou, J., Han, J.: Spatial clustering in the presence of obstacles. In: ICDE, pp. 359–367 (2001)

  14. Wang X., Hamilto H.J.: Clustering spatial data in the presence of obstacles. Int. J. Artif. Intell. Tools 14(1–2), 177–198 (2005)

    Article  Google Scholar 

  15. Wang, X., Rostoker, C., Hamilton, H.J.: Density-based spatial clustering in the presence of obstacles and facilitators. In: PKDD, pp. 446–458 (2004)

  16. Zaiane, O.R., Lee, C.H.: Clustering spatial data in the presence of obstacles: A density-based approach. In: IDEAS, pp. 214–223 (2002)

  17. Sharifzadeh M., Kolahdouzan M., Shahabi C.: The optimal sequenced route query. VLDB J. 17(4), 765–787 (2008)

    Article  Google Scholar 

  18. Sharifzadeh M., Shahabi C.: Processing optimal sequenced route queries using voronoi diagrams. GeoInformatica 12(4), 411–433 (2008)

    Article  Google Scholar 

  19. Li, F., Cheng, D., Hadjieleftheriou, M., Kollios, G., Teng, S.H.: On trip planning queries in spatial databases. In: SSTD, pp. 273–290 (2005)

  20. Beckmann, N., Kriegel, H.P., Schneider, R., Seeger, B.: The R*-tree: An efficient and robust access method for points and rectangles. In: SIGMOD, pp. 322–331 (1990)

  21. Guttman, A.: R-trees: A dynamic index structure for spatial searching. In: SIGMOD, pp. 47–54 (1984)

  22. Gao, Y., Zheng, B., Lee, W.C., Chen, G.: Continuous visible nearest neighbor queries. In: EDBT, pp. 144–155 (2009)

  23. Cheung K.L., Fu A.W.C.: Enhanced nearest neighbour search on the R-tree. SIGMOD Rec. 27(3), 16–21 (1998)

    Article  Google Scholar 

  24. Roussopoulos, N., Kelley, S., Vincent, F.: Nearest neighbor queries. In: SIGMOD, pp. 71–79 (1995)

  25. Papadopoulos, A., Manolopoulos, Y.: Performance of nearest neighbor queries in R-trees. In: ICDT, pp. 394–408 (1997)

  26. Henrich, A.: A distance-scan algorithm for spatial access structures. In: GIS, pp. 136–143 (1994)

  27. Hjaltason G.R., Samet H.: Distance browsing in spatial databases. ACM Trans. Database Syst. 24(2), 265–318 (1999)

    Article  Google Scholar 

  28. Ferhatosmanoglu, H., Stanoi, I., Agrawal, D., Abbadi, A.: Constrained nearest neighbor queries. In: SSTD, pp. 257–278 (2001)

  29. Papadias, D., Shen, Q., Tao, Y., Mouratidis, K.: Group nearest neighbor queries. In: ICDE, pp. 301–312 (2004)

  30. Papadias D., Tao Y., Mouratidis K., Hui K.: Aggregate nearest neighbor queries in spatial databases. ACM Trans. Database Syst. 30(2), 529–576 (2005)

    Article  Google Scholar 

  31. Zhang, J., Mamoulis, N., Papadias, D., Tao, Y.: All-nearest- neighbors queries in spatial databases. In: SSDBM, pp. 297–306 (2004)

  32. Deng, K., Zhou, X., Shen, H., Xu, K., Lin, X.: Surface k-NN query processing. In: ICDE, p. 78 (2006)

  33. Hu H., Lee D.L.: Range nearest-neighbor query. IEEE Trans. Knowl. Data Eng. 18(1), 78–91 (2006)

    Article  MathSciNet  Google Scholar 

  34. Sistla, A.P., Wolfson, O., Chamberlain, S., Dao, S.: Modeling and querying moving objects. In: ICDE, pp. 422–432 (1997)

  35. Iwerks, G.S., Samet, H., Smith, K.: Continuous k-nearest neighbor queries for continuously moving points with updates. In: VLDB, pp. 512–523 (2003)

  36. Li, Y., Yang, J., Han, J.: Continuous k-nearest neighbor search for moving objects. In: SSDBM, pp. 123–126 (2004)

  37. Mouratidis, K., Hadjieleftheriou, M., Papadias, D.: Conceptual partitioning: An efficient method for continuous nearest neighbor monitoring. In: SIGMOD, pp. 634–645 (2005)

  38. 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)

  39. Yu, X., Pu, K., Koudas, N.: Monitoring k-nearest neighbor queries over moving objects. In: ICDE, pp. 631–642 (2005)

  40. Liu, F., Hua, K.A., Do, T.T.: A P2P technique for continuous k-nearest-neighbor query in road networks. In: DEXA, pp. 264–276 (2007)

  41. Mouratidis, K., Yiu, M., Papadias, D., Mamoulis, N.: Continuous nearest neighbor monitoring in road networks. In: VLDB, pp. 43–54 (2006)

  42. Mouratidis K., Papadias D., Bakiras S., Tao Y.: A threshold-based algorithm for continuous monitoring of k nearest neighbors. IEEE Transactions on Knowledge and Data Engineering 17(11), 1451–1464 (2005)

    Article  Google Scholar 

  43. Wu, W., Guo, W., Tan, K.L.: Distributed processing of moving k-nearest-neighbor query on moving objects. In: ICDE, pp. 1116–1125 (2007)

  44. Zheng B., Lee W.C., Lee D.L.: On searching continuous k nearest neighbors in wireless data broadcast systems. IEEE Trans. Mob. Comput. 6(7), 748–761 (2007)

    Article  Google Scholar 

  45. Feng, J., Watanabe, T.: A fast method for continuous nearest target objects query on road network. In: VSMM, pp. 182–191 (2002)

  46. Kolahdouzan M.R., Shahabi C.: Alternative solutions for continuous k nearest neighbor queries in spatial network databases. GeoInformatica 9(4), 321–341 (2005)

    Article  Google Scholar 

  47. Cho, H.J., Chung, C.W.: An efficient and scalable approach to CNN queries in a road network. In: VLDB, pp. 865–876 (2005)

  48. Asano, T., Ghosh, S.K., Shermer, T.C.: Visibility in the plane. In: Handbook of Computation Geometry. Elsevier, Amsterdam (2000)

  49. Kofler M., Gervautz M., Gruber M.: R-trees for organizing and visualizing 3D GIS databases. J. Vis. Comput. Animat. 11(3), 129–143 (2000)

    Article  Google Scholar 

  50. Shou, L., Chionh, C., Ruan, Y., Huang, Z., Tan, K.L.: Walking through a very large virtual environment in real-time. In: VLDB, pp. 401–410 (2001)

  51. Shou, L., Huang, Z., Tan, K.L.: HDoV-tree: The structure, the storage, the speed. In: ICDE, pp. 557–568 (2003)

  52. Tao Y., Papadias D., Lian X., Xiao X.: Multidimensional reverse kNN search. VLDB J. 16(3), 293–316 (2007)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

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

    Yunjun Gao, Gencai Chen & Xiaofa Guo

  2. School of Information Systems, Singapore Management University, Singapore, Singapore

    Baihua Zheng

  3. Department of Computer Science, City University of Hong Kong, Hong Kong, China

    Qing Li

Authors
  1. Yunjun Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Baihua Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gencai Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Qing Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xiaofa Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yunjun Gao.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gao, Y., Zheng, B., Chen, G. et al. Continuous visible nearest neighbor query processing in spatial databases. The VLDB Journal 20, 371–396 (2011). https://doi.org/10.1007/s00778-010-0200-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00778-010-0200-z

Keywords

Search

Navigation