CONSTRAINT-BASED CONTEXT MODELING AND MANAGEMENT FOR PERSONALIZED MOBILE SYSTEMS
Keywords:Context-aware system, consistency constraint, context model, reasoning engine, mobile system
The capability of adapting to environmental changes and fulfilling specific needs of nomadic users empowers mobile devices with new value-added features. Users on the move are expecting real time and personalized services that are adjusted to their needs and that fit within their current time and space settings. Context-aware systems are distinguished by: i) their ability to profile users; ii) their awareness about device capabilities; and iii) their environmental knowledge. The availability of wireless networks supports context-aware systems through ubiquitous sensors and web services used to gather contextual information in order to offer users exceptional interactive experiences. In order to cope with information overload, collected data on the changing environmental context needs efficient management. In this research, we present a constraint-based context management system which handles efficiently complex situations in adopting a desired behaviour whenever a specific change occurs in the environment. This is accomplished through a set of knowledge-based rules which validate the consistency of the context by monitoring system constraints to trigger automatic context updates. We evaluate our dynamic context-consideration approach through real-life scenarios while comparing three consistency-validation strategies.
Charland A., Leroux B., Mobile Application Development: Web vs. Native Communications of the ACM, 54 (5), May 2011, 49-53.
Schilit B., Mobile Computing: Looking to the Future, Computer, 44 (5), May 2011, 28-29.
Anderson, J. Q., Rainie, L., The future of the Internet III. Pew Internet and American Life Project. 2008, Retrieved March 26, 2011, from http://www.pewinternet.org/ Reports/2008/ The-Futureofthe-Internet-III.aspx.
Berri, J., Benlamri, R., Context-Aware Mobile Search Engine, Next Generation Search Engines: Advanced Models for Information Retrieval, IGI Global, 2012, 371-385.
Desclés, J. –P., Langages applicatifs, langues naturelles et cognition, Hermès, Paris, 1990.
Givón, T., Context As Other Minds: The Pragmatics of Sociality, Cognition and Communication, John Benjamins, Amsterdam, 2005.
Lukowicz, P., Pentland, A., Ferscha A., From Context Awareness to Socially Aware Computing”, IEEE Pervasive Computing, 11 (1), March 2012, 32-41.
Dey, A. K., Understanding and Using Context, Personal and Ubiquitous Computing J., 5 (1), 2001, 5-7.
Bellavista, P., Corradi, A., Fanelli, M., Foschinia, L., Survey of Context Data Distribution for Mobile Ubiquitous Systems, ACM Computing Surveys (CSUR) Surveys, 44(4), 2012.
Yang W H, Liu Y P, Xu C, et al. A survey on dependability improvement techniques for pervasive computing systems. Sci China Inf Sci, 2015, 58: 052102(14), doi: 10.1007/s11432-015-5300-3
Xu, Chang, Cheung, S. C., Chan, W. K. and Ye, Chunyang, Partial constraint checking for context consistency in pervasive computing. ACM Trans. Softw. Eng. Methodol. 19(3), 2010, 1–61.
Hong, J., Suh, E.-H., Kim, J., Kim S., Context-aware system for proactive personalized service based on context history, Expert Systems with Applications, 36, 2009, 7448–7457.
Oh, Y., Han, J., Woo, W., A Context Management Architecture for Large-Scale Smart Environments, IEEE Communications Magazine, 48 (3), March 2010, 118-126.
Viktoriya Degeler, Alexander Lazovik, Reduced Context Consistency Diagrams for Resolving Inconsistent Data, ICST Transactions on Ubiquitous Environments, Volume 12, Issue 10-12, October-December 2012.
Bu, Yingyi, Chen, Shaxun, Li, Jun, Tao, Xianping and Lu, Jian, Context Consistency Management Using Ontology Based Model, Lecture Notes in Computer Science 4254, 2006, 741–755.
Lu, H., Chan, W., and Tse, T., Testing pervasive software in the presence of context inconsistency resolution services. In Proc. Of International Conference on Software engineering (ICSE’08), May 10–18, Leipzig, Germany, 2008, pp. 61–70.
Berri, J., Benlamri, R., Atif, Y., Ontology-Based Framework for Context-aware Mobile Learning, In International Conference on Wireless Communication and Mobile Computing, Vancouver, Canada, 3-6 July, 2006, 1307-1310.
Basaeed, E. I., Berri, J., Zemerly, J., Benlamri, R., Learner-Centric Context-Aware Mobile Learning, IEEE Multidisciplinary Engineering Education Magazine, 2 (2), June 2007, 30-33.
Russel, S. J., Norvig, P., Artificial Intelligence: A Modern Approach, 3rd Edition, Prentice Hall, N. J. USA, 2010.
Brown P. J., The Stick-e Document: a framework for creating context-aware applications. Proceedings of the Electronic Publishing ’96, 259-272. Laxenburg, Austria: IFIP, 1996.
Hull R., Neaves, P. & Bedford-Roberts, J. (1997). Towards situated computing. Proceedings of the 1st International Symposium on Wearable Computers (ISWC'97), 146-153. Los Alamitos, CA: IEEE.
Anind K. Dey, Gregory D. Abowd and Daniel Salber, A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications, Journal of Human-Computer Interaction, Springer, 16 (2), 2001, pp. 97-166.
Ward A., Jones, A. & Hopper, A., A new location technique for the active office. IEEE Personal Communications, 4(5), 1997, 42-47.
Rodden T., Cheverst, K., Davies, K. & Dix, A., Exploiting context in HCI design for mobile systems. Proceedings of the Workshop on Human Computer Interaction with Mobile Devices, Glasgow, Scotland, 1998.
Echtibi, A., Zemerly, M. J., Berri, J., A Service-Based Mobile Tourist Advisor, International Journal of Computer Information Systems and Industrial Management Applications, Vol. 1, 2009, 177-187.
Jawad Berri, Context Reasoning for Mobile Systems, International Conference on Computer Information Systems (ICCIS'2014), Sousse, Tunisia, January 17-19, 2014.
Hill, E. F., Jess in Action: Java Rule-Based Systems. Manning Publications Co., Greenwich, CT, USA, 2003.
Winston, P., Horn's, B., LISP 3rd edition, Addison Wesley, 1989.
Schildt, H., Java A Beginner's Guide, 5th Edition, McGraw Hill/Osborne, 2011.