(4) Scalability. Different road networks have different scales and different object
distribution densities, and the scale and object distribution density of the same
regional road network are also increasing. The scalability of the query method is
very important. Currently, recently neighboring technology scalability needs to be
further improved.
Acknowledgements. This work is supported by the National Natural Science Foundation of
China under Grant (No. 61371090, No. 61602076 and No. 61702072), the China Postdoctoral
Science Foundation Funded Project (2017M621122 and 2017M611211), the Natural Science
Foundation of Liaoning Province (No. 20170540144, No. 20170540232 and No. 20180540003)
and the Fundamental Research Funds for the Central Universities (No. 3132017118,
No. 3132017121 and No. 3132017123).
References
1. Zhiming D, Guo L, Li X, et al (2008) Data model and continuous query processing of
location dependent data based on object-relational database model. J Comput Res Dev 45
(Suppl.):88–94 (in Chinese)
2. Qiao SJ, Han N, Wang C, Zhu F, Tang CJ (2014) A two-tiered dynamic index structure of
moving objects based on constrained networks. Chin J Comput (9)
3. Donald K (1973) The art of computer programming, vol 3. Addison-Wesley Professional,
Indianapolis
4. Roussopoulos N, Kelley S, Vincent F (1995) Nearest neighbor queries. In: ACM sigmod
record, 24(2):71–79. https://doi.org/10.1145/223784.223794
5. Zhu H, Yang X, Wang B, et al (2016) Range-based obstructed nearest neighbor queries. In:
Proceedings of the SIGMOD, pp 2053–2068. https://doi.org/10.1145/2882903.2915234
6. Zeberga K, Cho HJ, Chung TS (2014) A safe-region approach to k-RNN queries in directed
road network. In: Proceedings of the IEEE international conference on computational
science and engineering (CSE), pp 818–824
7. Cho HJ, Chung CW (2005) An efficient and scalable approach to CNN queries in a road
network. In: Proceedings of the VLDB, pp 865–876
8. Yiu M, Mamoulis N, Papadias D (2005) Aggregate nearest neighbor queries in road
networks. TKDE 17(6): 820–833
9. Almeida VTD (2004) Indexing the trajectories of moving objects in networks. In:
Proceedings of the IEEE scientific and statistical database management international
conference, pp 115–115. https://doi.org/10.1109/ssdm.2004.1311200
10. Feng J, Zhu YL, Mukai N, Watanabe T (2007) Search on transportation networks for
location-based service. Appl Intell 26(1):69–79. https://doi.org/10.1007/s10489-006-0004-4
11. Tao Y, Papadias D, Lian X (2004) Reverse kNN search in arbitrary dimensionality. In:
Processing of the 30th VLDB Conference, Canada, Toronto, pp 744–755
12. Papadias D, Zhang J, Mamoulis N, Tao Y (2003) Query processing in spatial network
databases. VLDB 2003:802–813
13. Kolahdouzan M, Shahabi C (2004) Voronoi-based k nearest neighbor search for spatial
network databases. In: VLDB’04 Proceedings of the thirtieth international conference on
very large data bases, pp 840–851
A Survey of Moving Objects kNN Query …
635
distribution densities, and the scale and object distribution density of the same
regional road network are also increasing. The scalability of the query method is
very important. Currently, recently neighboring technology scalability needs to be
further improved.
Acknowledgements. This work is supported by the National Natural Science Foundation of
China under Grant (No. 61371090, No. 61602076 and No. 61702072), the China Postdoctoral
Science Foundation Funded Project (2017M621122 and 2017M611211), the Natural Science
Foundation of Liaoning Province (No. 20170540144, No. 20170540232 and No. 20180540003)
and the Fundamental Research Funds for the Central Universities (No. 3132017118,
No. 3132017121 and No. 3132017123).
References
1. Zhiming D, Guo L, Li X, et al (2008) Data model and continuous query processing of
location dependent data based on object-relational database model. J Comput Res Dev 45
(Suppl.):88–94 (in Chinese)
2. Qiao SJ, Han N, Wang C, Zhu F, Tang CJ (2014) A two-tiered dynamic index structure of
moving objects based on constrained networks. Chin J Comput (9)
3. Donald K (1973) The art of computer programming, vol 3. Addison-Wesley Professional,
Indianapolis
4. Roussopoulos N, Kelley S, Vincent F (1995) Nearest neighbor queries. In: ACM sigmod
record, 24(2):71–79. https://doi.org/10.1145/223784.223794
5. Zhu H, Yang X, Wang B, et al (2016) Range-based obstructed nearest neighbor queries. In:
Proceedings of the SIGMOD, pp 2053–2068. https://doi.org/10.1145/2882903.2915234
6. Zeberga K, Cho HJ, Chung TS (2014) A safe-region approach to k-RNN queries in directed
road network. In: Proceedings of the IEEE international conference on computational
science and engineering (CSE), pp 818–824
7. Cho HJ, Chung CW (2005) An efficient and scalable approach to CNN queries in a road
network. In: Proceedings of the VLDB, pp 865–876
8. Yiu M, Mamoulis N, Papadias D (2005) Aggregate nearest neighbor queries in road
networks. TKDE 17(6): 820–833
9. Almeida VTD (2004) Indexing the trajectories of moving objects in networks. In:
Proceedings of the IEEE scientific and statistical database management international
conference, pp 115–115. https://doi.org/10.1109/ssdm.2004.1311200
10. Feng J, Zhu YL, Mukai N, Watanabe T (2007) Search on transportation networks for
location-based service. Appl Intell 26(1):69–79. https://doi.org/10.1007/s10489-006-0004-4
11. Tao Y, Papadias D, Lian X (2004) Reverse kNN search in arbitrary dimensionality. In:
Processing of the 30th VLDB Conference, Canada, Toronto, pp 744–755
12. Papadias D, Zhang J, Mamoulis N, Tao Y (2003) Query processing in spatial network
databases. VLDB 2003:802–813
13. Kolahdouzan M, Shahabi C (2004) Voronoi-based k nearest neighbor search for spatial
network databases. In: VLDB’04 Proceedings of the thirtieth international conference on
very large data bases, pp 840–851
A Survey of Moving Objects kNN Query …
635