skip to main content
research-article

Query Indexing and Velocity Constrained Indexing: Scalable Techniques for Continuous Queries on Moving Objects

Published: 01 October 2002 Publication History

Abstract

Moving object environments are characterized by large numbers of moving objects and numerous concurrent continuous queries over these objects. Efficient evaluation of these queries in response to the movement of the objects is critical for supporting acceptable response times. In such environments, the traditional approach of building an index on the objects (data) suffers from the need for frequent updates and thereby results in poor performance. In fact, a brute force, no-index strategy yields better performance in many cases. Neither the traditional approach nor the brute force strategy achieve reasonable query processing times. This paper develops novel techniques for the efficient and scalable evaluation of multiple continuous queries on moving objects. Our solution leverages two complimentary techniques: Query Indexing and Velocity Constrained Indexing (VCI). Query Indexing relies on 1) incremental evaluation, 2) reversing the role of queries and data, and 3) exploiting the relative locations of objects and queries. VCI takes advantage of the maximum possible speed of objects in order to delay the expensive operation of updating an index to reflect the movement of objects. In contrast to an earlier technique [29] that requires exact knowledge about the movement of the objects, VCI does not rely on such information. While Query Indexing outperforms VCI, it does not efficiently handle the arrival of new queries. Velocity constrained indexing, on the other hand, is unaffected by changes in queries. We demonstrate that a combination of Query Indexing and Velocity Constrained Indexing enables the scalable execution of insertion and deletion of queries in addition to processing ongoing queries. We also develop several optimizations and present a detailed experimental evaluation of our techniques. The experimental results show that the proposed schemes outperform the traditional approaches by almost two orders of magnitude.

References

[1]
S. Acharya M.J. Franklin and S. Zdonik, “Disseminating Updates on Broadcast Disks,” Proc. 22nd Int'l Conf. Very Large Data Bases, T.M. Vijayaraman et al., eds., pp. 354-365, Sept. 1996.
[2]
S. Acharya R. Alonso M.J. Franklin and S.B. Zdonik, “Broadcast Disks: Data Management for Asymmetric Communications Environments,” Proc. 1995 ACM SIGMOD Int'l Conf. Management of Data, pp. 199-210, May 1995.
[3]
P.K. Agarwal L. Arge and J. Erickson, “Indexing Moving Points,” Proc. 2000 ACM SIGACT-SIGMOD-SIGART Symp. Principles of Database Systems (PODS), May 2000.
[4]
A. Aggarwal and S. Suri, “Fast Algorithms for Computing the Largest Empty Rectangle,” Proc. Third Symp. Computational Geometry, pp. 278-290, 1987.
[5]
A. Aggarwal and J. Wein, “Computational Geometry,” Lecture Notes for MIT, 1988.
[6]
N. Amenta, “Bounded Boxes, Hausdorff Distance, and a New Proof of an Interesting Helly-Type Theorem,” Proc. Symp. Computational Geometry, pp. 340-347, 1994.
[7]
W.G. Aref S.E. Hambrusch and S. Prabhakar, “Information Management in a Ubiquitous Global Positioning Environment,” Technical Report 00-006, Dept. of Computer Sciences, Purdue Univ., West Lafayette, Ind., Feb. 2000.
[8]
B. Becker S. Gschwind T. Ohler B. Seeger and P. Widmayer, “An Asymptotically Optimal Multiversion B-Tree,” The VLDB J., vol. 5, no. 4, pp. 264-275, Dec. 1996.
[9]
N. Beckmann H. Kriegel R. Schneider and B. Seeger, “The R*-Tree: An Efficient and Robust Access Method for Points and Rectangles,” Proc. ACM SIGMOD Int'l Conf. Management of Data, pp. 322-331, May 1990.
[10]
T.H. Cormen C.E. Leiserson and R.L. Rivest, Introduction to Algorithms. New York: McGraw-Hill, 1990.
[11]
US Wireless Corp., “The Market Potential of the Wireless Location Industry,” http://www.uswcorp.com/USWCMainPages/laby.htm, 2001.
[12]
L. Forlizzi R.H. Guting E. Nardelli and M. Scheider, “A Data Model and Data Structures for Moving Objects Databases,” Proc. ACM SIGMOD Conf., May 2000.
[13]
R.H. Guting M.H. Bohlen M. Erwig C.S. Jensen N.A. Lorentzos M. Schneider and M. Vazirgiannis, “A Foundation for Representing and Querying Moving Objects,” ACM Trans. Database Systems, 2000.
[14]
S.E. Hambrusch C.-M. Liu W. Aref and S. Prabhakar, “Query Processing in Broadcasted Spatial Index Trees,” Proc. Seventh Int'l Symp. Spatial and Temporal Databases (SSTD 2001), July 2001.
[15]
Q. Hu W.-C. Lee and D.L. Lee, “Power Conservative Multi-Attribute Queries on Data Broadcast,” Proc. Int'l Conf. Data Eng. (ICDE), pp. 157-166, 2000.
[16]
Q. Hu W.-C. Lee and D.L. Lee, “A Hybrid Index Technique for Power Efficient Data Broadcast,” Distributed and Parallel Databases, vol. 9, no. 2, pp. 151-177, 2001.
[17]
T. Imielinski S. Viswanathan and B.R. Badrinath, “Energy Efficient Indexing on Air,” Proc. Int'l Conf. Management of Data, R.T. Snodgrass and M. Winslett, eds., pp. 25-36, May 1994.
[18]
G. Kollios D. Gunopulos and V.J. Tsotras, “On Indexing Mobile Objects,” Proc. 1999 ACM SIGACT-SIGMOD-SIGART Symp. Principles of Database Systems (PODS), June 1999.
[19]
H. Koshima and J. Hoshen, “Personal Locator Services Emerge,” IEEE Spectrum, vol. 37, no. 2, pp. 41-48, Feb. 2000.
[20]
A. Kumar V.J. Tsotras and C. Faloutsos, “Designing Access Methods for Bitemporal Databases,” IEEE Trans. Knowledge and Data Eng., vol. 10, no. 1, pp. 1-20, 1998.
[21]
Trimble Navigation Ltd., “Trimble Customer Solutions,” http://www.trimble.com/solution/index.htm, 1999.
[22]
M. McKenna J. O'Rourke and S. Suri, “Finding the Largest Rectangle in an Orthogonal Polygon,” Proc. 23rd Allerton Conf. Comm., Control, and Computing, pp. 486-495, 1985.
[23]
Rand McNally, “Streetfinder GPS for Palm IIIc Connected Organizer,” http://www.randmcnally.com/palmIIIc/index.ehtml#receiver, 2001.
[24]
D. Pfoser and C.S. Jensen, “Capturing the Uncertainty of Moving-Objects Representations,” Proc. SSDBM Conf., pp. 123-132, 1999.
[25]
D. Pfoser C.S. Jensen and Y. Theodoridis, “Novel Approaches in Query Processing for Moving Objects,” Proc. 26th Int'l Conf. Very Large Databases (VLDB), Sept. 2000.
[26]
D. Pfoser Y. Theodoridis and C.S. Jensen, “Indexing Trajectories of Moving Point Objects,” Technical Report CH-99-3, Chorochronos Technical Report, June 1999.
[27]
N. Roussopoulos S. Kelley and F. Vincent, “Nearest Neighbor Queries,” Proc. ACM SIGMOD Int'l Conf. Management of Data, pp. 71-79, 1995.
[28]
W. Aref S. Hambrusch and S. Prabhakar, “Pervasive Location-Aware Computing Enviroments,” http://www.cs.purdue.edu/place, 2001.
[29]
S. Saltenis C. Jensen S. Leutenegger and M. Lopez, “Indexing the Position of Continuously Moving Objects,” Proc. ACM SIGMOD Conf., May 2000.
[30]
H. Samet, The Design and Analysis of Spatial Data Structures. Reading, Mass.: Addison-Wesley, 1990.
[31]
A.P. Sistla O. Wolfson S. Chamberlain and S. Dao, “Modeling and Querying Moving Objects,” Proc. 14th Int'l Conf. Data Eng. (ICDE '97), pp. 422-432, 1997.
[32]
J. Tayeb Ö. Ulusoy and O. Wolfson, “A Quadtree-Based Dynamic Attribute Indexing Method,” The Computer J., vol. 41, no. 3, pp. 185-200, 1998.
[33]
TruePosition, “What Is Trueposition Cellular Location System?” http://www.trueposition.com/intro.htm, 2001.
[34]
J. Werb and C. Lanzl, “Designing a Positioning System for Finding Things and People Indoors,” IEEE Spectrum, vol. 35, no. 9, pp. 71-78, Sept. 1998.
[35]
O. Wolfson, “Research Issues on Moving Object Databases (Tutorial),” Proc. ACM SIGMOD Conf., p. 581, May 2000.
[36]
O. Wolfson S. Chamberlain S. Dao L. Jiang and G. Mendez, “Cost and Imprecision in Modeling the Position of Moving Objects,” Proc. 14th Int'l Conf. Data Eng. (ICDE '98), Feb. 1998.
[37]
O. Wolfson P.A. Sistla S. Chamberlain and Y. Yesha, “Updating and Querying Databases that Track Mobile Units,” Distributed and Parallel Databases, vol. 7, no. 3, pp. 257-387, 1999.
[38]
O. Wolfson B. Xu S. Chamberlain and L. Jiang, “Moving Objects Databases: Issues and Solutions,” Proc. Scientific and Statistical Database Management (SSDBM) Conf., pp. 111-122, 1998.
[39]
J.M. Zagami S.A. Parl J.J. Bussgang and K.D. Melillo, “Providing Universal Location Services Using a Wireless e911 Location Network,” IEEE Comm. Magazine, Apr. 1998.
[40]
S. Zdonik M. Franklin R. Alonso and S. Acharya, “Are 'Disks in the Air' Just Pie in the Sky?” Proc. IEEE Workshop Mobile Computing Systems and Applications, Dec. 1994.

Cited By

View all

Recommendations

Comments

Information & Contributors

Information

Published In

cover image IEEE Transactions on Computers
IEEE Transactions on Computers  Volume 51, Issue 10
October 2002
161 pages

Publisher

IEEE Computer Society

United States

Publication History

Published: 01 October 2002

Author Tags

  1. Moving objects
  2. continuous queries
  3. query indexing.
  4. spatio-temporal indexing

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 01 Jan 2025

Other Metrics

Citations

Cited By

View all

View Options

View options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media