Research on Modeling and Indexing of Trajectories of Moving Objects in Road Networks

Article Preview

Abstract:

Proposed a new index structure, named MG2R*, can efficiently store and retrieve the past, present and future positions of network-constrained moving objects. It is a two-tier structure. The upper is a MultiGrid-R*-Tree (MGRT for short) that is used to index the road network. The lower is a group of independent R*-Tree. Each R*-Tree is relative to a route in the road network, can index the spatiotemporal trajectory of the moving objects in the road. Moreover, moving objects query is implemented based on this index structure. It compared to other index structures for road-network-based moving objects, such as MON-Tree, the experimental results shown that the MG2R* can effectively improve the query performance of the spatio-temporal trajectory of network-constrained moving objects.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 756-759)

Pages:

1234-1239

Citation:

Online since:

September 2013

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Ding Zhiming, Li Xiaonan, Yu Bo. Indexing the Historical, Current, and Future Locations of Network-Constrained Moving Objects [J]. Journal of Software, 200912(20): 3193-3204.

DOI: 10.3724/sp.j.1001.2009.03400

Google Scholar

[2] Huang Qunshan. Research and Implementation Of Digital map editing system and its supporting technology [D]. ZheJiang University. (2008).

Google Scholar

[3] Ding Z, Güting RH. Managing moving objects on dynamic transportation networks. In: Proc. of the 16th Int'l Conf. on Science and Statistical Database Management (SSDBM 2004). Santorin: IEEE Computer Society, 2004. 287−296.

DOI: 10.1109/ssdm.2004.1311220

Google Scholar

[4] T. Brinkhofi. A framework for generating network-based moving objects. GeoInformatica, 6(2): 153 - 180, (2002).

Google Scholar

[5] Chen J, Meng XF. Indexing future trajectories of moving objects in a constrained network. Journal of Computer Science and Technology, 2007, 22(2): 245−251.

DOI: 10.1007/s11390-007-9031-9

Google Scholar

[6] Guo J, Guo W, Zhou DR. Indexing approach for querying about present and future based on constrained moving objects in spatial-temporal databases. Journal of Chinese Computer Systems, 2007, 28(2): 128−131 (in Chinese with English abstract).

Google Scholar

[7] A. Guttman. R-trees: A Dynamic Index Structure for Spatial Searching. Proc. of theACM SIGMOD, Boston, MA, June 1984: 47-57.

DOI: 10.1145/971697.602266

Google Scholar

[8] Shi Shaoyu, Tang Xinming, Wu Fan, Lei Bing, Wang Huibing. Multi-level grid spatio-temporal index [J]. science of surveying and mapping, 20063(31): 54-55.

Google Scholar

[9] Hao Zhongxiao. Spatio-temporal Database Query and inference [M]. Beijing: Science Press, 2010: 6-7.

Google Scholar

[10] T. K. Sellis,N. Roussopoulos,C. Faloutsos. The R*-tree:A Dynamic Index for Multidimensional Objects. Proceedings of the Thirteenth International Conference on Very Large Data Bases:t987 13th VLDB,Brighton,UK,1987. Los Altos,CA,USA, Morgan Kauthaarm, 1987: 507-518.

Google Scholar

[11] D. Pfoser,Indexing the Trajectories of Moving Objects. IEEE Data Engineering Bulletin, 2002, 25(2): 3-9.

Google Scholar

[12] http: /data. geocomm. com/catalog/c_index. html.

Google Scholar