CFP last date
20 January 2025
Reseach Article

A New Proposed Algorithm for OBBx-index Structure

by K. Appathurai, S. Karthikeyan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 50 - Number 11
Year of Publication: 2012
Authors: K. Appathurai, S. Karthikeyan
10.5120/7816-1103

K. Appathurai, S. Karthikeyan . A New Proposed Algorithm for OBBx-index Structure. International Journal of Computer Applications. 50, 11 ( July 2012), 32-36. DOI=10.5120/7816-1103

@article{ 10.5120/7816-1103,
author = { K. Appathurai, S. Karthikeyan },
title = { A New Proposed Algorithm for OBBx-index Structure },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 50 },
number = { 11 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 32-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume50/number11/7816-1103/ },
doi = { 10.5120/7816-1103 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:48:02.584350+05:30
%A K. Appathurai
%A S. Karthikeyan
%T A New Proposed Algorithm for OBBx-index Structure
%J International Journal of Computer Applications
%@ 0975-8887
%V 50
%N 11
%P 32-36
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Even though lot of spatio-temporal indexing techniques for moving objects are availed, some more intelligence has been given to the advance of techniques that professionally support queries about the past, present, and future positions of moving objects. This paper proposes the new index structure called POBBx (Parameterized Optimal BBx) which indexes the positions of moving objects, given as linear functions of time, at any time. The index supports queries that select objects based on temporal and spatial constraints, such as queries that retrieve all objects whose positions fall within a spatial range during a set of time intervals. The proposed work reduces lot of searching efforts done by the existing method and minimized time complexity. The simulation results shows that the proposed algorithm provides enhanced performance than OBBx index structure.

References
  1. Long-Van Nguyen-Dinh, Walid G. Aref, Mohamed F. Mokbel 2010. Spatio-Temporal Access Methods: Part 2 (2003 - 2010). Bulletin of the IEEE Computer SocietyTechnical Committee on Data Engineering
  2. M. Pelanis, S. ? Saltenis, and C. Jensen. Indexing the past, present, and anticipated future positions of moving objects. TODS, 31(1):255–298, 2006.
  3. Z. -H. Liu, X. -L. Liu, J. -W. Ge, and H. -Y. Bae. Indexing large moving objects from past to future with PCFI+-index. In COMAD, pages 131–137, 2005.
  4. V. Chakka, A. Everspaugh, and J. Patel. Indexing large trajectory data sets with SETI. In CIDR, 2003
  5. Y. Tao, D. Papadias, and J. Sun. The TPR*-tree: An optimized spatio-temporal access method for predictive queries. In VLDB, 2003.
  6. C. Jensen, D. Lin, and B. Ooi. Query and update efficient B+-tree based indexing of moving objects. In VLDB, 2004.
  7. M. Mokbel, T. Ghanem, andW. G. Aref. Spatio-temporal access methods. IEEE Data Eng. Bull. , 26(2):40–49, 2003.
  8. J. Ni and C. V. Ravishankar. PA-tree: A parametric indexing scheme for spatio-temporal trajectories. In SSTD, 2005.
  9. P. Zhou, D. Zhang, B. Salzberg, G. Cooperman, and G. Kollios. Close pair queries in moving object databases. In GIS, pages 2–11, 2005.
  10. Dan Lin, Christian S. Jensen, Beng Chin Ooi, Simonas S? altenis, BBx index :Efficient Indexing of the Historical, Present, and Future Positions of Moving Objects, MDM 2005 Ayia Napa Cyprus
  11. P. K. Agarwal and C. M. Procopiuc. Advances in Indexing for Mobile Objects. IEEE Data Eng. Bull. , 25(2): 25–34, 2002.
  12. G. Kollios, D. Gunopulos, V. J. Tsotras. On Indexing Mobile Objects. In Proc. PODS, pp. 261–272, 1999.
  13. K. Appathurai, Dr. S. Karthikeyan. A Survey on Spatiotemporal Access Methods. International Journal of Computer Appliations. Volume 18, No 4, 2011.
  14. Mohamed F. Mokbel, Xiaopeng Xiong, Moustafa A. Hammad, and Walid G. Aref, Continuous Query Processing of Spatio-temporal Data Streams in PLACE, 2004 Kluwer Academic Publishers. Printed in the Netherlands
  15. Su Chen • Beng Chin Ooi • Zhenjie Zhang, An Adaptive Updating Protocol for Reducing Moving Object Database Workload.
  16. Yongquan Xia, Weili Li , and Shaohui Ning, Moving Object Detection Algorithm Based on Variance Analysis, 2009, Second International Workshop on Computer Science and Engineering Qingdao, China
  17. Arash Gholami Rad, Abbas Dehghani and Mohamed Rehan Karim, Vehicle speed detection in video image sequences using CVS method, 2010, International Journal of the Physical Sciences Vol. 5(17), pp. 2555-2563.
  18. M. A. Nascimento and J. R. O. Silva. Towards Historical R-trees. In Proc. ACM Symposium on Applied Computing, pp. 235–240, 1998.
  19. Y. Tao and D. Papadias. MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries. In Proc. VLDB, pp. 431–440, 2001.
  20. J. Sun, D. Papadias, Y. Tao, and B. Liu. Querying about the Past, the Present, and the Future in Spatio-Temporal Databases. In Proc. ICDE, pp. 202–213, 2004.
  21. K. Appathurai, Dr. S. Karthikeyan (2012), "A New Proposed Algorithm for BBx-Index Structure", IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 3, No 1, May 2012
  22. K. Appathurai, Dr. S. Karthikeyan (2012), " A Novel Indexing Method for BBx- Index structure", Int. J. Computer Technology & Applications,Vol 3 (2), 779-784
Index Terms

Computer Science
Information Sciences

Keywords

Moving Objects POBBx index OBBx index Migration and BBx-trees