Advertisement

Context-Dependent Task Computing in Pervasive Environment

  • Hongbo Ni
  • Xingshe Zhou
  • Daqing Zhang
  • Ngoh Lek Heng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4239)

Abstract

Pervasive computing environments need to exhibit highly adaptive behavior to meet the changing personal requirements and operational context of environment. Recently, task computing (TC) paradigm has gained acceptance as the choice computing model for pervasive computing environment. One of the key components of TC is a task model that provides an adequate high-level description of user-oriented tasks. This paper presents a novel context-sensitive task modeling approach capable of supporting complex, user-oriented task definitions, and proposes an algorithm to discover a task and a method to execute it. This work is motivated by the fact that whilst current TC systems allow users to interact with their ambient environments in terms of high level tasks, existing task definitions are still relatively simple, and do not include user-centric and environmental contextual information in the task definition. This paper elaborates the proposed task model through a smart home application example to illustrate steps in context-dependent task modeling, service provisioning and resource organization.

Keywords

Context Information Task Model Pervasive Computing Task Computing User Context 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Weiser, M.: Some Computer Science Issues in Ubiquitous Computing. Communication. Communications of the ACM 36(7), 75–84 (1993)CrossRefGoogle Scholar
  2. 2.
    Castro, P., Muntz, R.: Managing Context Data for Smart Spaces. IEEE Personal Communications 7, 44–46 (2000)CrossRefGoogle Scholar
  3. 3.
    Prekop, P., Burnett, M.: Activities, Context and Ubiquitous Computing. Computer Communications 26(11), 1168–1176 (2003)CrossRefGoogle Scholar
  4. 4.
    Heckmann, D.: Introducing Situational Statements as an integrating Data Structure for User Modeling, Context-Awareness and Resource-Adaptive Computing. In: ABIS Workshop on adaptivity and user modeling in interactive software systems (2003)Google Scholar
  5. 5.
    Tang, T.Y., McCalla, G.: Smart Recommendation for an Evolving E-Learning System. In: AIED 2003, vol. 10, pp. 699–711 (2003)Google Scholar
  6. 6.
    Jakobsen, C.S., Warthoe, S.: Adaptive Design Implications for Knowledge Organization and Information Retrieval Systems. In: Nord I&D, Knowledge and Change, pp. 58–61 (2004)Google Scholar
  7. 7.
    Kay, J.: The um toolkit for cooperative user modeling. User Modeling and User-Adapted Interaction 3, 149–196 (1995)Google Scholar
  8. 8.
    Shareef, A.F., Kinshuk: Student Model for Distance Education System in Maldives. In: Rossett, A. (ed.) Proceedings of E-Learn 2003 (Phoenix, Arizona, USA), Norfolk, VA, USA: November 7-11, 2003, pp. 2435–2438. AACE, Norfolk (2003)Google Scholar
  9. 9.
    Yu, Z., Zhang, D., Zhou, X.-s., Li, C.: User Preference Learning for Multimedia Personalization in Pervasive Computing Environment. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds.) KES 2005. LNCS, vol. 3682, pp. 236–242. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  10. 10.
    Wang, Z., Garlan, D.: Task-driven computing., Technical Report, NO. CMU-CS-00-154, Carnegie Mellon University (May 2000), http://www-2.cs.cmu.edu/~aura/docdir/wang00.pdf
  11. 11.
    Masuoka, R., Parsia, B., Labrou, Y.: Task Computing – The Semantic Web Meets Pervasive Computing. In: Fensel, D., Sycara, K.P., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, pp. 866–881. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  12. 12.
    Dey, A.K., Abowd, G.D.: Towards a Better Understanding of Context and Context-Awareness. College of Computing, Georgia Institute of Technology, Atlanta GA USA, Technical Report GIT-GVU-99-22 (1999)Google Scholar
  13. 13.
    Firby, R.J., Kahn, R.E., Prokopowicz, P.N., Swain, M.J.: An architecture for vision and action. In: Fourteenth International Joint Conference on Artificial Intelligence, pp. 72–81 (1995)Google Scholar
  14. 14.
    Firby, R.J.: Task networks for controlling continuous processes. In: Proceedings of the Second International Conference on Artificial Intelligence Planning Systems, pp. 49–54 (1994)Google Scholar
  15. 15.
    Wang, X.H., Zhang, D.Q., Pung, H.K.: Ontology Based Context Modeling and Reasoning using OWL. In: Workshop Proceedings of the 2nd IEEE Conference on Pervasive Computing and Communications (PerCom 2004), pp. 18–22 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hongbo Ni
    • 1
  • Xingshe Zhou
    • 1
  • Daqing Zhang
    • 2
  • Ngoh Lek Heng
    • 2
  1. 1.School of Computer ScienceNorthwestern Polytechnic UniversityChina
  2. 2.Context Aware System DepartmentInstitute for Infocomm ResearchSingapore

Personalised recommendations