Advertisement

GeoInformatica

, Volume 17, Issue 1, pp 63–95 | Cite as

Continuous aggregate nearest neighbor queries

  • Hicham G. ElmonguiEmail author
  • Mohamed F. Mokbel
  • Walid G. Aref
Article

Abstract

This paper addresses the problem of continuous aggregate nearest-neighbor (CANN) queries for moving objects in spatio-temporal data stream management systems. A CANN query specifies a set of landmarks, an integer k, and an aggregate distance function f (e.g., min, max, or sum), where f computes the aggregate distance between a moving object and each of the landmarks. The answer to this continuous query is the set of k moving objects that have the smallest aggregate distance f. A CANN query may also be viewed as a combined set of nearest neighbor queries. We introduce several algorithms to continuously and incrementally answer CANN queries. Extensive experimentation shows that the proposed operators outperform the state-of-the-art algorithms by up to a factor of 3 and incur low memory overhead.

Keywords

Continuous query Spatio-temporal query Aggregate nearest neighbor 

References

  1. 1.
    Open Optimization Library. http://ool.sourceforge.net/
  2. 2.
    LOPTI - Mathematical Optimization Library. http://volnitsky.com/project/lopti/
  3. 3.
  4. 4.
  5. 5.
    Extreme Optimization Numerical Libraries for .NET. http://www.extremeoptimization.com/
  6. 6.
    Bentley JL, Yao AC-C (1976) An almost optimal algorithm for unbounded searching. Inf Process Lett:5(3):82–87CrossRefGoogle Scholar
  7. 7.
    Brinkhoff T (2002) A framework for generating network based moving objects. Geoinformatica 6(2):153–180CrossRefGoogle Scholar
  8. 8.
    Cai Y, Hua KA, Cao G (2004) Processing range-monitoring queries on heterogeneous mobile objects. In: Proceedings of the international conference on mobile data management, MDMGoogle Scholar
  9. 9.
    Cho H-J, Chung C-W (2005) An efficient and scalable approach to CNN queries in a road network. In: Proceedings of the international conference on very large data bases, VLDB, pp 865–876, Trondheim, NorwayGoogle Scholar
  10. 10.
    Düntgen C, Behr T, Güting RH (2009) BerlinMOD: a benchmark for moving object databases. VLDB J (The International Journal on Very Large Data Bases) 18(6):1335–1368CrossRefGoogle Scholar
  11. 11.
    Elmongui HG, Mokbel MF, Aref WG (2005) Spatio-temporal histograms. In: Proceedings of the international symposium on advances in spatial and temporal databases, SSTDGoogle Scholar
  12. 12.
    Gedik B, Liu L (2004) MobiEyes: distributed processing of continuously moving queries on moving objects in a mobile system. In: Proceedings of the international conference on extending database technology, EDBTGoogle Scholar
  13. 13.
    Hadjieleftheriou M, Kollios G, Gunopulos D, Tsotras VJ (2003) On-line discovery of dense areas in spatio-temporal databases. In: Proceedings of the international symposium on advances in spatial and temporal databases, SSTD, pp 306–324, Santorini Island, GreeceGoogle Scholar
  14. 14.
    Hu H, Xu J, Lee DL (2005) A generic framework for monitoring continuous spatial queries over moving objects. In: Proceedings of the ACM international conference on management of data, SIGMODGoogle Scholar
  15. 15.
    Huang Z, Lu H, Ooi BC, Tung AK (2006) Continuous skyline queries for moving objects. IEEE Trans Knowl Data Eng (TKDE) 18(12):1645–1658CrossRefGoogle Scholar
  16. 16.
    Iwerks GS, Samet H, Smith K (2003) Continuous K-nearest neighbor queries for continuously moving points with updates. In: Proceedings of the international conference on very large data bases, VLDB, pp 512–523, Berlin, GermanyGoogle Scholar
  17. 17.
    Jensen CS, Lin D, Ooi BC (2004) Query and update efficient B  + -tree based indexing of moving objects. In: Proceedings of the international conference on very large data bases, VLDBGoogle Scholar
  18. 18.
    Jensen CS, Lin D, Ooi BC, Zhang R (2006) Effective density queries on continuously moving objects. In: Proceedings of the international conference on data engineering, ICDE, Atlanta, GAGoogle Scholar
  19. 19.
    Kang J, Mokbel MF, Shekhar S, Xia T, Zhang D (2007) Continuous evaluation of monochromatic and bichromatic reverse nearest neighbors. In: Proceedings of the international conference on data engineering, ICDE, pp 806–815, Istanbul, TurkeyGoogle Scholar
  20. 20.
    Lazaridis I, Porkaew K, Mehrotra S (2002) Dynamic queries over mobile objects. In: Proceedings of the international conference on extending database technology, EDBTGoogle Scholar
  21. 21.
    Li H, Lu H, Huang B, Huang Z (2005) Two ellipse-based pruning methods for group nearest neighbor queries. In: Proceedings of the ACM symposium on advances in geographic information systems, ACM GIS.Google Scholar
  22. 22.
    Mokbel MF, Aref WG (2005) GPAC: generic and progressive processing of mobile queries over mobile data. In: Proceedings of the international conference on mobile data management, MDMGoogle Scholar
  23. 23.
    Mokbel MF, Aref WG (2005) PLACE: a scalable location-aware database server for spatiotemporal data streams. Data Eng Bull 28(3):3–10Google Scholar
  24. 24.
    Mokbel MF, Aref WG (2008) SOLE: scalable online execution of continuous queries on spatio-temporal data streams. VLDB J (The International Journal on Very Large Data Bases) 17(5):971–995CrossRefGoogle Scholar
  25. 25.
    Mokbel MF, Xiong X, Aref WG (2004) SINA: scalable incremental processing of continuous queries in spatio-temporal databases. In Proceedings of the ACM international conference on management of data, SIGMODGoogle Scholar
  26. 26.
    Mouratidis K, Papadias D, Hadjieleftheriou M (2005) Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring. In: Proceedings of the ACM international conference on management of data, SIGMODGoogle Scholar
  27. 27.
    Mouratidis K, Yiu ML, Papadias D, Mamoulis N (2006) Continuous nearest neighbor monitoring in road networks. In: Proceedings of the international conference on very large data bases, VLDB, pp 43–54, Seoul, KoreaGoogle Scholar
  28. 28.
    Papadias D, Shen Q, Tao Y, Mouratidis K (2004) Group nearest neighbor queries. In: Proceedings of the international conference on data engineering, ICDEGoogle Scholar
  29. 29.
    Papadias D, Tao Y, Mouratidis K, Hui CK (2005) Aggregate nearest neighbor queries in spatial databases. ACM Trans Database Syst (TODS) 30(2):529–576CrossRefGoogle Scholar
  30. 30.
    Song Z, Roussopoulos N (2001) K-nearest neighbor search for moving query point. In: Proceedings of the international symposium on advances in spatial and temporal databases, SSTDGoogle Scholar
  31. 31.
    Tao Y, Papadias D (2003) Spatial queries in dynamic environments. ACM Trans Database Syst (TODS) 28(2):101–139CrossRefGoogle Scholar
  32. 32.
    Tao Y, Papadias D, Shen Q (2002) Continuous nearest neighbor search. In: Proceedings of the international conference on very large data bases, VLDBGoogle Scholar
  33. 33.
    U LH, Mamoulis N, Yiu ML (2007) Continuous monitoring of exclusive closest pairs. In: Proceedings of the international symposium on advances in spatial and temporal databases, SSTD, Boston, MAGoogle Scholar
  34. 34.
    Xia T, Zhang D (2006) Continuous reverse nearest neighbor monitoring. In: Proceedings of the international conference on data engineering, ICDE, Atlanta, GAGoogle Scholar
  35. 35.
    Xiong X, Mokbel MF, Aref WG (2005) SEA-CNN: scalable processing of continuous K-nearest neighbor queries in spatio-temporal databases. In: Proceedings of the international conference on data engineering, ICDEGoogle Scholar
  36. 36.
    Yiu ML, Mamoulis N, Papadias D (2005) Aggregate nearest neighbor queries in road networks. IEEE Trans Knowl Data Eng (TKDE) 17(6):820–833CrossRefGoogle Scholar
  37. 37.
    Yu X, Pu KQ, Koudas N (2005) Monitoring K-nearest neighbor queries over moving objects. In: Proceedings of the international conference on data engineering, ICDEGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Hicham G. Elmongui
    • 1
    Email author
  • Mohamed F. Mokbel
    • 2
  • Walid G. Aref
    • 3
  1. 1.Department of Computer and Systems Engineering, Faculty of EngineeringAlexandria UniversityAlexandriaEgypt
  2. 2.Department of Computer Science and EngineeringUniversity of Minnesota - Twin CitiesMinneapolisUSA
  3. 3.Department of Computer SciencePurdue UniversityWest LafayetteUSA

Personalised recommendations