A Hybrid Location Model with a Computable Location Identifier for Ubiquitous Computing

  • Changhao Jiang
  • Peter Steenkiste
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2498)


Location modeling and representation are crucial technologies for context-aware applications. In this paper, we present a novel location model combining the virtues of both the hierarchical and coordinate location models, and we introduce a computable location identifier, namely Aura Location Identifier (ALI). We then describe how the Aura space service uses this hybrid model to handle spatial queries for context-aware applications. A simple example of such a query is a range query, e.g. “select name from printer where distance(location, ‘ali://cmu/wean-hall/floor3/3100-corridor#(10,10,0)’) <10”, where “location” is an attribute representing the location of printers. Finally, we discuss how we extended the PostgreSQL database system to provide direct support for spatial SQL queries at the database level. These extensions improve performance and increase flexibility for context-aware applications.


Ubiquitous Computing Range Query Space Tree Contextual Service Spatial Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bahl, P., AND Padmanabhan, V. N. Radar: An in-building rf-based user locationand tracking system. In Proc. IEEE Infocom (Tel Aviv, Israel, March 2000).Google Scholar
  2. 2.
    Bauer, M., Becker, C., AND Rothermel, K. Location models from the perspectiveof context-aware applications and mobile ad hoc networks. In Workshopon Location Modeling for Ubiquitous Computing (2001).Google Scholar
  3. 3.
    Universal Resource Identifiers (URI): Generic Syntax, August 1998.Google Scholar
  4. 4.
    Brumitt, B., AND Shafer, S. Topological world modeling using semantic spaces. In Workshop on Location Modeling for Ubiquitous Computing (2001).Google Scholar
  5. 5.
    Domnitcheva, S. Location modeling: State of the art and challegnes. In Workshop on Location Modeling for Ubiquitous Computing (2001).Google Scholar
  6. 6.
    Garlan, D., Siewiorek, D., Smailagic, A., AND Steenkiste, P. Project Aura:Towards Distraction-Free Pervasive Computing. IEEE Pervasive Computing 1, 2(April-June 2002), 22–31.Google Scholar
  7. 7.
    Hohl, F. U. Kubach, A. Leonhardi, Rothermel, K., AND Schwehm, M.Nexus-an open global infrastructure for spatial-aware applications. In Proceedings of MobiCom (Seattle, USA, 1999).Google Scholar
  8. 8.
    Judd, G., AND Steenkiste, P. Providing Contextual Information to UbiquitousComputing Applications. Technical Report CMU-CS-02-154, Department ofComputer Science, Carnegie Mellon University, July 2002.Google Scholar
  9. 9.
    O’connell, T., Jensen, P., Dey, A., AND Abowd, G. Location in the awarehome. In Workshop on Location Modeling for Ubiquitous Computing (2001).Google Scholar
  10. 10.
    Postgresql. Software available from
  11. 11.
    Smailagic, A., AND Kogan, D. Location Sensing in a Context Aware ComputingEnvironment. IEEE Wireless Communications 9, 3 (June 2002).Google Scholar
  12. 12.
    Stonebraker, M. Inclusion of new types in relational data base systems. In Proceedings of the International Conference on Data Engineering, (Los Angeles, CA, feb 1986), vol. IEEE Computer Society Order Number 655, IEEE Computer Society Press, pp. 262–269.Google Scholar
  13. 13.
    Stonebraker, M., AND Kemnits, G. The postgres next-generation databasemanagement system. In Communications of the ACM (Oct 1991), vol. 34, pp. 78–92.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Changhao Jiang
    • 1
  • Peter Steenkiste
    • 2
  1. 1.Computer Science DepartmentCarnegie Mellon UniversityPittsburghUSA
  2. 2.Department of Electrical and Computer EngineeringCarnegie Mellon UniversityPittsburghUSA

Personalised recommendations