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Continuous queries on trajectories of moving objects

Published:08 August 2012Publication History

ABSTRACT

Since navigation systems and tracking devices are becoming ubiquitous in our daily life, the development of efficient methods for processing massive sets of mobile objects are of utmost importance. Although future routes of mobile objects are often known in advance in many applications, this information is not fully utilized in most methods so far. In this paper, we reveal the beneficial effects of exploiting future routes for the early generation of the expected results of spatio-temporal queries. This kind of probable results is important for operative analytics in many applications like smart fleet management or intelligent logistics. For efficiently computing the high number of future trajectory points, a new index structure is presented which allows for a fast maintenance of query results under continuous changes of mobile objects. Our methods make use of specific update patterns, which require substantially less maintenance costs than the most general case of an update. A set of experiments based on a commonly used simulation environment shows the efficiency of our approach.

References

  1. Jeung, H., Yiu, M. L., Zhou, X., Jensen, C. S., Shen, H. T.: Discovery of convoys in trajectory databases. Proc. VLDB Endow. 1(1) (2008) 1068--1080 Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Patroumpas, K., Sellis, T. K.: Managing trajectories of moving objects as data streams. STDBM. (2004) 41--48Google ScholarGoogle Scholar
  3. Schmiegelt, P., Seeger, B.: Querying the future of spatio-temporal objects. In: ACM GIS. GIS "10, New York, NY, USA, ACM (2010) 486--489 Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Krämer, J., Seeger, B.: Pipes - a public infrastructure for processing and exploring streams. ACM SIGMOD. (2004) 925--926 Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Krämer, J., Seeger, B.: Semantics and implementation of continuous sliding window queries over data streams. ACM TODS. 34(1) (2009) 1--49 Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Lin, D., Cui, B., Yang, D.: Optimizing moving queries over moving object data streams. DASFAA. (2007) 563--575 Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Samet, H.: The Design and Analysis of Spatial Data Structures (Addison-Wesley series in computer science). Addison-Wesley Pub. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. šaltenis, S., Jensen, C. S., Leutenegger, S. T., Lopez, M. A.: Indexing the positions of continuously moving objects. SIGMOD Rec. 29(2) (2000) 331--342 Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. šidlauskas, D., šaltenis, S., Christiansen, C. W., Johansen, J. M., šaulys, D.: Trees or grids?: indexing moving objects in main memory. ACM GIS. (2009) 236--245 Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Brinkhoff, T., Str, O.: A framework for generating network-based moving objects. Geoinformatica 6 (2002) 2002 Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Bercken, J., Blohsfeld, B., Dittrich, J. P., Krämer, J., Schäfer, T., Schneider, M., Seeger, B.: XXL - A Library Approach to Supporting Efficient Implementations of Advanced Database Queries. VLDB. (2001) 39--48 Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Iwerks, G. S., Samet, H., Smith, K. P.: Maintenance of k-nn and spatial join queries on continuously moving points. ACM TODS. 31(2) (2006) 485--536 Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. R. Z., Lin, D., Ramamohanarao, K., Bertino, E.: Continuous intersection joins over moving objects. ICDE. (2008) 863--872 Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Patel, J. M., Chen, Y., Chakka, V. P.: Stripes: An efficient index for predicted trajectories. ACM SIGMOD. (2004) 637--646 Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Jensen, C. S., Lin, D., Ooi, B. C.: Query and update efficient b + -tree based indexing of moving objects. VLDB. (2004) 768--779 Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Yiu, M. L., Tao, Y., Mamoulis, N.: The bdual-tree: indexing moving objects by space filling curves in the dual space. The VLDB Journal 17(3) (2008) 379--400 Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Nehme, R. V., Rundensteiner, E. A.: Scuba: Scalable cluster-based algorithm for evaluating continuous spatio-temporal queries on moving objects. EDBT. (2006) 1001--1019 Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Mokbel, M. F., Xiong, X., Hammad, M. A., Aref, W. G.: Continuous query processing of spatio-temporal data streams in place. Geoinformatica 9(4) (2005) 343--365 Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Mokbel, M. F., Xiong, X., Aref, W. G.: Sina: Scalable incremental processing of continuous queries in spatio-temporal databases. ACM SIGMOD. (2004) 623--634 Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Liu, L.: Mobieyes: Distributed processing of continuously moving queries on moving objects in a mobile system. EDBT. (2004) 67--87Google ScholarGoogle Scholar
  21. Tao, Y., Papadias, D., Sun, J.: The tpr*-tree: An optimized spatio-temporal access method for predictive queries. VLDB. (2003) 790--801 Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Trajcevski, G., Wolfson, O., Hinrichs, K., Chamberlain, S.: Managing uncertainty in moving objects databases. ACM TODS. 29(3) (2004) 463--507 Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Ding, H., Trajcevski, G., Scheuermann, P.: Efficient maintenance of continuous queries for trajectories. Geoinformatica 12(3) (2008) 255--288 Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Chon, H. D., Agrawal, D., El Abbadi, A.: Range and knn query processing for moving objects in grid model. Mob. Netw. Appl. 8(4) (2003) 401--412 Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Hadjieleftheriou, M., Kollios, G., Tsotras, J., Gunopulos, D.: Indexing spatiotemporal archives. The VLDB Journal 15(2) (2006) 143--164 Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. De Almeida, V. T., Güting, R. H.: Indexing the trajectories of moving objects in networks*. Geoinformatica 9(1) (2005) 33--60 Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Dittrich, J., Blunschi, L., Vaz Salles, M. A.: Indexing moving objects using short-lived throwaway indexes. SSTD. (2009) 189--207 Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Continuous queries on trajectories of moving objects

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      • Published in

        cover image ACM Other conferences
        IDEAS '12: Proceedings of the 16th International Database Engineering & Applications Sysmposium
        August 2012
        261 pages
        ISBN:9781450312349
        DOI:10.1145/2351476

        Copyright © 2012 ACM

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        New York, NY, United States

        Publication History

        • Published: 8 August 2012

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