Context-Dependent Task Computing in Pervasive Environment
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.
KeywordsContext Information Task Model Pervasive Computing Task Computing User Context
Unable to display preview. Download preview PDF.
- 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.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.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.Kay, J.: The um toolkit for cooperative user modeling. User Modeling and User-Adapted Interaction 3, 149–196 (1995)Google Scholar
- 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
- 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
- 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.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.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.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