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Spatio-temporal Queries on Road Networks, Coding Based Methods

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Encyclopedia of GIS

Synonyms

Spatial and spatio-temporal queries over moving objects; Spatio-temporal network coding

Definition

Coding-based techniques assign codes to intersections on road networks, so that shortest distance between intersections can be determined very quickly as Hamming distances (1950) between their codes. Conventional methods have been used when distances between objects are defined under the Euclidean metric, but coding-based methods are superior for join, range, intercept, and other spatial and spatiotemporal queries when distances are measured along the roads.

The coding is obtained by embedding the graph metric into a higher-dimensional space, such as a hypercube of a suitable dimension. As an example, Fig. 3 depicts the labels for nodes from the sample road network in Fig. 1, obtained using an isometric embedding of the road network into a hypercube of dimension 14.

Typical spatiotemporal range queries have the form “Find all objects that are in region R during a time interval [t...

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References

  • Agarwal PK, Arge L, Erickson J (2000) Indexing moving points. In: Proceedings of the 19th ACM symposium on principles of database systems (PODS), Dallas, pp 175–186

    Google Scholar 

  • Chen CX, Zaniolo C (2000) SQL ST: a spatio-temporal data model and query language. In: International conference on conceptual modeling/the entity relationship approach, pp 96–111

    Google Scholar 

  • Christine P, Spaccapietra S, Zimnyi E (1999) Spatio-temporal conceptual models: data structures + space + time. In: GIS ’99: proceedings of the 7th ACM international symposium on advances in geographic information systems, ACM Press, New York, pp 26–33

    Google Scholar 

  • Cormen TH, Leiserson CE, Rivest RL (1990) Introduction to algorithms. MIT Press/McGraw-Hill, Cambridge/London

    MATH  Google Scholar 

  • Erwig M, Guting RH, Schneider M, Vazirgiannis M (1999) Spatio-temporal data types: an approach to modeling and querying moving objects in databases. Geoinformatica 3(3):269–296

    Article  Google Scholar 

  • Forlizzi L, Guting R, Nardelli E, Schneider M (2000) A data model and data structures for moving objects databases. In: Proceedings of ACM SIGMOD, Dallas, pp 319–330

    Google Scholar 

  • Frederickson GN (1987) Fast algorithms for shortest paths in planar graphs, with applications. SIAM J Comput 16(6):1004–1022

    Article  MathSciNet  MATH  Google Scholar 

  • Gavoille C, Peleg D, Perennes S, Raz R (2001) Distance labeling in graphs. In: Symposium on Discrete Algorithms, Philadelphia, pp 210–219

    MATH  Google Scholar 

  • Gupta S, Kopparty S, Ravishankar C (2004) Roads, codes, and spatiotemporal queries. In: PODS ’04: proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on principles of database systems. ACM Press, New York, pp 115–124

    Chapter  Google Scholar 

  • Hamming RW (1950) Error-detecting and error-correcting codes. Bell Syst Tech J 29(2):147–160

    Article  MathSciNet  Google Scholar 

  • Jensen CS, Lin D, Ooi BC (2004) Query and update efficient b+-tree based indexing of moving objects. In: VLDB, Toronto, pp 768–779

    Google Scholar 

  • Kollios G, Gunopulos D, Tsotras V (1999) On Indexing Mobile Objects. In: Proceedings of the 18th ACM symposium on principles of database systems (PODS), Philadelphia, pp. 261–272,

    Google Scholar 

  • Prabhakar S, Xia Y, Kalashnikov D, Aref W, Hambrusch S (2002) Query indexing and velocity constrained indexing: scalable techniques for continuous queries on moving objects. IEEE Trans Comput 51(10): 1124–1140

    Article  MathSciNet  Google Scholar 

  • Saltenis S, Jensen C, Leutenegger S, Lopez MA (2000) Indexing the positions of continuously moving objects. In: Proceedings of the ACM SIGMOD, Dallas, pp 331–342

    Google Scholar 

  • Sistla A, Wolfton O, Chamberlain S, Dao S (1997) Modeling and querying moving objects. In: Proceedings of the 13th international conference on data engineering (ICDE’97). IEEE, Washington/Brussels/Tokyo, pp 422–433

    Chapter  Google Scholar 

  • Tao Y, Papadias D, Sun J (2003) The tpr*-tree: an optimized spatio-temporal access method for predictive queries. In: Proceedings of the VLDB, Berlin/Germany

    Book  Google Scholar 

  • US Census Bureau. TIGER. http://tiger.census.gov/

  • Wolfson O (2002) Moving objects information management: the database challenge. In: NGITS ’02: proceedings of the 5th international workshop on next generation information technologies and systems. Springer, London, pp 75–89

    Chapter  Google Scholar 

  • Zhou P, Zhang D, Salzberg B, Cooperman G, Kollios G (2005) Close pair queries in moving object databases. In: GIS ’05: proceedings of the 13th annual ACM international workshop on geographic information systems. ACM Press, New York, pp 2–11

    Chapter  Google Scholar 

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Gupta, S., Ravishankar, C.V. (2016). Spatio-temporal Queries on Road Networks, Coding Based Methods. In: Shekhar, S., Xiong, H., Zhou, X. (eds) Encyclopedia of GIS. Springer, Cham. https://doi.org/10.1007/978-3-319-23519-6_1330-2

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