Versatile Safe-Region Generation Method for Continuous Monitoring of Moving Objects in the Road Network Distance

  • Yutaka OhsawaEmail author
  • Htoo Htoo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9645)


This paper proposes a fast safe-region generation method for several kinds of vicinity queries including distance range queries, set k nearest neighbor (NN) queries, and ordered kNN queries. When a user is driving a car on a road network, he/she wants to know objects located in a vicinity of the car. However, the result is changing according to the movement of the car, and therefore, the up-to-date result is always expected, and requested to the server. On the other hand, frequent requests for updating results to the server cause heavy loading. To cope with this problem efficiently, the idea of safe-region has been proposed. This paper proposes a fast generation method of the safe-region applicable to several types of vicinity queries. Through experimental evaluations, the proposed algorithm achieves a great performance in terms of processing times, and is one or two orders of magnitude faster than existing algorithms.


Road Network Data Object Road Segment Near Neighbor Range Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The present study was partially supported by the Japanese Ministry of Education, Science, Sports and Culture (Grant-in-Aid Scientific Research (C) 15K00147).


  1. 1.
    Gedik, B., Liu, L.: MobiEyes: distributed processing of continuously moving queries on moving objects in a mobile system. In: Bertino, E., Christodoulakis, S., Plexousakis, D., Christophides, V., Koubarakis, M., Böhm, K. (eds.) EDBT 2004. LNCS, vol. 2992, pp. 67–87. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  2. 2.
    Prabhakar, S., Xia, Y., Kalashnikov, D., Aref, W., Hambrush, S.: Query indexing and velocity constrained indexing: scalable techniques for continuous queries on moving objects. IEEE Trans. Comput. 51(10), 1124–1140 (2002)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Mouratidis, K., Yiu, M.L., Papadias, D., Mamoulis, N.: Continuous nearest neighbor monitoring in road networks. In: Proceedings of the 32nd VLDB, pp. 43–54 (2006)Google Scholar
  4. 4.
    Bentis, R., Jensen, C.S., Karčlauskas, G., Šaltenis, S.: Nearest and reverse nearest neighbor queries for moving objects. VLDB J. 15(3), 229–250 (2006)CrossRefGoogle Scholar
  5. 5.
    Xia, T., Zhang, D.: Continuous reverse nearest neighbor monitoring. In: Proceeding of the 22nd International Conference on Data Engineering, p. 77 (2006)Google Scholar
  6. 6.
    Iwerks, G.S., Samet, H., Smith, K.P.: Maintenance of spatial semijoin queries on moving points. In: Proceedings of VLDB (2004)Google Scholar
  7. 7.
    Chen, Z., Shen, H.T., Zhou, X., Yu, J.X.: Monitoring path nearest neighbor in road networks. In: SIGMOD 2009, pp. 591–602 (2009)Google Scholar
  8. 8.
    Huang, Y.K., Chang, C.H., Lee, C.: Continuous distance-based skyline queries in road networks. Inf. Syst. 37, 611–633 (2012)CrossRefGoogle Scholar
  9. 9.
    Stojanovic, D., Papadopoulos, A.N., Predic, B., Djordjevic-Kajan, S., Nanopoulos, A.: Continuous range monitoring of mobile objects in road network. Data Knowl. Eng. 64, 77–100 (2007)CrossRefGoogle Scholar
  10. 10.
    Cheema, M.A., Lin, X., Zhang, W., Mhang, Y.: Influence zone: efficiently processing reverse \(k\) nearest neighbors queries. In: Proceeding ICDE, pp. 577–588 (2011)Google Scholar
  11. 11.
    Cheema, M.A., Zhang, W., Lin, X., Zhang, Y., Li, X.: Continuous reverse k nearest neighbors queries in Euclidean space and in spatial networks. VLDB J. 21, 69–95 (2012)CrossRefGoogle Scholar
  12. 12.
    Liu, F., Do, T.T., Hua, K.A.: Dynamic range query in spatial network environments. In: Bressan, S., Küng, J., Wagner, R. (eds.) DEXA 2006. LNCS, vol. 4080, pp. 254–265. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Yiu, M.L., Papadias, D., Mamoulis, N., Tao, Y.: Reverse nearest neighbor in large graphs. IEEE Trans. Knowl. Data Eng. 18(4), 1–14 (2006)CrossRefGoogle Scholar
  14. 14.
    Cheema, M.A., Brankovic, L., Lin, X., Zhang, W., Wang, W.: Continuous monitoring of distance based range queries. IEEE Trans. Knowl. Data Eng. 23, 1182–1199 (2011)CrossRefGoogle Scholar
  15. 15.
    Papadias, D., Zhang, J., Mamoulis, N., Tao, Y.: Query processing in spatial network databases. In: Proceedings of 29th VLDB, pp. 790–801 (2003)Google Scholar
  16. 16.
    Htoo, H., Ohsawa, Y., Sonehara, N., Sakauchi, M.: Incremental single-source multi target A* algorithm for LBS based on road network distance. IEICE Trans. Inf. Syst. E96–D(5), 1043–1052 (2013)CrossRefGoogle Scholar
  17. 17.
    Cho, H.J., Kwon, S.J., Chung, T.S.: A safe exit algorithm for continuous nearest neighbor monitoring in road networks. Mobile Inf. Syst. 9, 37–53 (2013)CrossRefGoogle Scholar
  18. 18.
    Cho, H.J., Chung, C.W.: An efficient and scalable approach to CNN queries in a road network. In: Proceedings of the 31st International Conference on Very Large Data Bases, pp. 805–876 (2005)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Graduate School of Science and EngineeringSaitama UniversitySaitamaJapan

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