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Continuous Constraint Query Evaluation for Spatiotemporal Streams

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Book cover Advances in Spatial and Temporal Databases (SSTD 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4605))

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Abstract

In this paper we study the evaluation of continuous constraint queries (CCQs) for spatiotemporal streams. A CCQ triggers an alert whenever a configuration of constraints between streaming events in space and time are satisfied. Consider, for instance, a server that receives updates from GPS-enabled agents that report their positions and other measurements (e.g., environmental readings). An example of CCQ is: “Alert whenever at least 5 readings closer than 5km to each other and within a time difference of 5 minutes report high pressures and low temperatures”. We model CCQs as Constraint Satisfaction Problems (CSPs) and develop solutions for their continuous evaluation. Our techniques (1) consider the fast arrival rate of incoming events, and (2) minimize the memory requirements, without using predefined window constraints, but by utilizing the structure of the queries. In order to show the merits of the proposed techniques, we implement a system prototype and evaluate it with real data.

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References

  1. CCQ system prototype, http://www.cs.ucr.edu/~marioh/ccq

  2. AOML. Global Drifter Center, http://www.aoml.noaa.gov/phod/dac/gdc.html

  3. Bessière, C., Régin, J.C.: Refining the basic constraint propagation algorithm. In: Proc. of the International Joint Conference on Artificial Intelligence (IJCAI), pp. 309–315 (2001)

    Google Scholar 

  4. Bitner, J.R., Reingold, E.: Backtracking programming techniques. Communications of the ACM (CACM) 18(11), 651–656 (1975)

    Article  MATH  Google Scholar 

  5. Cai, Y., Hua, K.A., Cao, G.: Processing range-monitoring queries on heterogeneous mobile objects. In: Proc. of the International Conference on Mobile Data Management (MDM), pp. 27–38 (2004)

    Google Scholar 

  6. Chandrasekaran, S., Franklin, M.J.: Streaming queries over streaming data. In: Proc. of Very Large Data Bases (VLDB) (2002)

    Google Scholar 

  7. Dechter, R., Meiri, I., Pearl, J.: Temporal constraint networks. Journal of Artificial Intelligence 49(1-3), 61–95 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  8. Gaschnig, J.: Experimental case studies of backtrack vs. waltz-type vs. new algorithms for satisficing assignment problems. In: Proc. of the Canadian Artificial Intelligence Conference, pp. 268–277 (1978)

    Google Scholar 

  9. Gedik, B., Liu, L.: MobiEyes: Distributed processing of continuously moving queries on moving objects in a mobile system. In: Proc. of Extending Database Technology (EDBT), pp. 67–87 (2004)

    Google Scholar 

  10. Guttman, A.: R-trees: A dynamic index structure for spatial searching. In: Proc. of ACM Management of Data (SIGMOD), pp. 47–57. ACM Press, New York (1984)

    Google Scholar 

  11. Hadjieleftheriou, M., Hoel, E., Tsotras, V.J.: Sail: A library for efficient application integration of spatial indices. In: Proc. of Scientific and Statistical Database Management (SSDBM) (2004)

    Google Scholar 

  12. Hammad, M.A., Aref, W.G., Elmagarmid, A.K.: Stream window join: Tracking moving objects in sensor-network databases. In: Proc. of Scientific and Statistical Database Management (SSDBM), pp. 75–84 (2003)

    Google Scholar 

  13. Hanson, E., Carnes, C., Huang, L., Konyala, M., Noronha, L., Parthasarathy, S., Park, J., Vernon, A.: Scalable trigger processing. In: Proc. of International Conference on Data Engineering (ICDE), pp. 266–275 (1999)

    Google Scholar 

  14. Haralick, M., Elliot, J.: Increasing tree-search efficiency for constraint satisfaction problems. Journal of Artificial Intelligence 14(3), 263–313 (1980)

    Article  Google Scholar 

  15. Keidl, M., Kreutz, A., Kemper, A., Kossmann, D.: A publish & subscribe architecture for distributed metadata management. In: Proc. of International Conference on Data Engineering (ICDE), pp. 309–320 (2002)

    Google Scholar 

  16. Kumar, V.: Algorithms for constraints satisfaction problems: A survey. The AI Magazine 13(1), 32–44 (1992)

    Google Scholar 

  17. Lazaridis, I., Porkaew, K., Mehrotra, S.: Dynamic queries over mobile objects. In: Proc. of Extending Database Technology (EDBT) (2002)

    Google Scholar 

  18. Lee, M.-L., Hsu, W., Jensen, C.S., Teo, K.L.: Supporting frequent updates in R-Trees: A bottom-up approach. In: Proc. of Very Large Data Bases (VLDB) (2003)

    Google Scholar 

  19. Papadimitriou, C., Grigni, M., Papadias, D.: Topological inference. In: Proc. of the International Joint Conference of Artificial Intelligence (IJCAI) (1995)

    Google Scholar 

  20. Madden, S., Shah, M., Hellerstein, J., Raman, V.: Continuously adaptive continuous queries over streams. In: SIGMOD. Proc. of ACM Management of Data, ACM Press, New York (2002)

    Google Scholar 

  21. Mamoulis, N., Papadias, D.: Multiway spatial joins. ACM Transactions on Database Systems (TODS) 26(4), 424–475 (2001)

    Article  MATH  Google Scholar 

  22. Mamoulis, N., Yiu, M.L.: Non-contiguous sequence pattern queries. In: Proc. of Extending Database Technology (EDBT), pp. 783–800 (2004)

    Google Scholar 

  23. Mokbel, M.F., Xiong, X., Aref, W.G.: SINA: Scalable incremental processing of continuous queries in spatiotemporal databases. In: SIGMOD. Proc. of ACM Management of Data, ACM Press, New York (2004)

    Google Scholar 

  24. Papadias, D., Mamoulis, N., Delis, V.: Algorithms for querying by spatial structure. In: Proc. of Very Large Data Bases (VLDB), pp. 546–557 (1998)

    Google Scholar 

  25. Pei, J., Han, J., Wang, W.: Mining sequential patterns with constraints in large databases. In: Proc. of Conference on Information and Knowledge Management (CIKM) (2002)

    Google Scholar 

  26. PMEL. Tropical Atmosphere Ocean Project, http://www.pmel.noaa.gov/tao

  27. Prabhakar, S., Xia, Y., Kalashnikov, D., Aref, W.G., Hambrusch, S.E.: Query indexing and velocity constraint indexing: Scalable techniques for continuous queries on moving objects. IEEE Transactions on Computers 51(10), 1–17 (2002)

    Article  MathSciNet  Google Scholar 

  28. Six, H., Widmayer, P.: Spatial searching in geometric databases. In: Proc. of International Conference on Data Engineering (ICDE), pp. 496–503 (1988)

    Google Scholar 

  29. Song, Z., Roussopoulos, N.: K-nearest neighbor search for moving query point. In: Proc. of Symposium on Advances in Spatial and Temporal Databases (SSTD), pp. 79–96 (2001)

    Google Scholar 

  30. Stonebraker, M., Sellis, T.K., Hanson, E.N.: An analysis of rule indexing implementations in data base systems. In: Expert Database Conference, pp. 465–476 (1986)

    Google Scholar 

  31. Tao, Y., Papadias, D., Shen, Q.: Continuous nearest neighbor search. In: Proc. of Very Large Data Bases (VLDB), pp. 287–298 (2002)

    Google Scholar 

  32. Teng, W.-G., Chen, M.-S., Yu, P.S.: A regression-based temporal pattern mining scheme for data s treams. In: Proc. of Very Large Data Bases (VLDB) (2003)

    Google Scholar 

  33. Tsang, E.P.K.: Foundations of Constraint Satisfaction. Academic Press, London and San Diego (1993)

    Google Scholar 

  34. Yan, T.W., Garcia-Molina, H.: The sift information dissemination system. In: TODS. ACM Transactions on Database Systems, pp. 529–565. ACM Press, New York (1999)

    Google Scholar 

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Author information

Authors and Affiliations

  1. AT&T Labs Inc., 180 Park Avenue, Florham Park, NJ 07932,  

    Marios Hadjieleftheriou

  2. Department of Computer Science, University of Hong Kong, Pokfulam Road, Hong Kong,  

    Nikos Mamoulis

  3. Department of Computer Science and Engineering, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong,  

    Yufei Tao

Authors
  1. Marios Hadjieleftheriou
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  2. Nikos Mamoulis
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  3. Yufei Tao
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Editor information

Dimitris Papadias Donghui Zhang George Kollios

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© 2007 Springer-Verlag Berlin Heidelberg

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Hadjieleftheriou, M., Mamoulis, N., Tao, Y. (2007). Continuous Constraint Query Evaluation for Spatiotemporal Streams. In: Papadias, D., Zhang, D., Kollios, G. (eds) Advances in Spatial and Temporal Databases. SSTD 2007. Lecture Notes in Computer Science, vol 4605. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73540-3_20

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  • DOI: https://doi.org/10.1007/978-3-540-73540-3_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73539-7

  • Online ISBN: 978-3-540-73540-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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