Towards a Standards-Based Autonomic Context Management System

  • Jadwiga Indulska
  • Karen Henricksen
  • Peizhao Hu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4158)


Pervasive computing applications must be sufficiently autonomous to adapt their behaviour to changes in computing resources and user requirements. This capability is known as context-awareness. In some cases, context-aware applications must be implemented as autonomic systems which are capable of dynamically discovering and replacing context sources (sensors) at run-time. Unlike other types of application autonomy, this kind of dynamic reconfiguration has not been sufficiently investigated yet by the research community. However, application-level context models are becoming common, in order to ease programming of context-aware applications and support evolution by decoupling applications from context sources. We can leverage these context models to develop general (i.e., application-independent) solutions for dynamic, run-time discovery of context sources (i.e., context management). This paper presents a model and architecture for a reconfigurable context management system that supports interoperability by building on emerging standards for sensor description and classification.


Sensor Network Context Information Recognition Event Context Management Open Geospatial Consortium 
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.


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  1. 1.
    Strang, T., Linnhoff-Popien, C.: A context modeling survey. In: UbiComp 1st International Workshop on Advanced Context Modelling, Reasoning and Management, Nottingham (September 2004)Google Scholar
  2. 2.
    Henricksen, K., Indulska, J., Rakotonirainy, A.: Modeling context information in pervasive computing systems. In: Mattern, F., Naghshineh, M. (eds.) PERVASIVE 2002. LNCS, vol. 2414, pp. 167–180. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  3. 3.
    Henricksen, K., Indulska, J.: Developing context-aware pervasive computing applications: Models and approach. Journal of Pervasive and Mobile Computing 2, 37–64 (2006)CrossRefGoogle Scholar
  4. 4.
    Henricksen, K., Indulska, J., McFadden, T., Balasubramaniam, S.: Middleware for Distributed Context-Aware Systems. In: Meersman, R., Tari, Z. (eds.) OTM 2005. LNCS, vol. 3760, pp. 846–863. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  5. 5.
    Dey, A.K., Salber, D., Abowd, G.D.: A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Human-Computer Interaction 16, 97–166 (2001)CrossRefGoogle Scholar
  6. 6.
    Chen, G., Li, M., Kotz, D.: Design and implementation of a large-scale context fusion network. In: 1st Annual International Conference on Mobile and Ubiquitous Systems (MobiQuitous), pp. 246–255. IEEE Computer Society Press, Los Alamitos (2004)CrossRefGoogle Scholar
  7. 7.
    Lim, A.: Distributed services for information dissemination in self-organizing sensor networks. Journal of the Franklin Institute 338, 707–727 (2001)zbMATHCrossRefGoogle Scholar
  8. 8.
    Polastre, J., Hill, J., Culler, D.: Versatile low power media access for wireless sensor networks. In: 2nd International Conference on Embedded Networked Sensor Systems, Baltimore, pp. 95–107 (2004)Google Scholar
  9. 9.
    Shah, R.C., Rabaey, J.M.: Energy aware routing for low energy ad hoc sensor networks. In: Wireless Communications and Networking Conference (WCNC), vol. 1, pp. 350–355 (2002)Google Scholar
  10. 10.
    Yao, Y., Gehrke, J.: Query processing for sensor networks. In: 1st Biennial Conference on Innovative Data Systems Research (CIDR), Asilomar (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jadwiga Indulska
    • 1
  • Karen Henricksen
    • 1
  • Peizhao Hu
    • 1
  1. 1.School of Information Technology and Electrical EngineeringThe University of Queensland, and, National ICT Australia (NICTA) 

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