Abstract
The convergence of several trends, including the proliferation of mobile, cloud technologies, social media, and socio-economic trends such as bring your own device, have led to not only the democratization of computing but also to information overload. This creates an opportunity for pattern recognition and ‘Big Data’ technologies to support mobile ‘context-aware’ computing where technology understands human intentions, and effectively ‘disappears’. In this short paper we explore, through the development of an Android-based test application, one of the capabilities of this computing paradigm, which to the best of our knowledge has not been explored. Namely, we explore the complexity of dynamic calendar based minimum path computing.
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Notes
Please note that the challenges described in this paper still apply with recent versions of Android.
References
Chen, G., Kotz, D. (2000). A survey of context-aware mobile computing research. Technical Report, Dartmouth College. [Online]: http://www.cs.dartmouth.edu/reports/TR2000-381.pdf.
Tabatabaei, S., Gluhak, A., & Tafazolli, R. (2013). A survey on smartphone-based systems for opportunistic user context recognition. ACM Computing Surveys, 45(3), 27.
Pejovic, V., Musolesi, M. (2013). Anticipatory mobile computing: A survey of the state of the art and research challenges. University of Birmingham Technical Report CSR-13-02, December.
Bokharouss, I., Wobcke, W., Yiu-Wa, C., Limaru, A., Wong, A. (2007). A location-aware mobile call handling assistant. In Proceedings of the 21st IEEE international conference on advanced information networking and applications workshops (AINAW), 2007, Vol. 2, pp. 282–289.
Roth, J. Context-aware apps with the Zonezz platform. In Proceedings of the 3rd ACM SOSP workshop on networking, systems, and applications on mobile handhelds (MobiHeld ’11).
[Online]: http://www.openhandsetalliance.com/android_overview.html.
[Online]:http://developer.android.com/about/versions/android-2.3-highlights.html.
[Online]: http://developer.android.com/guide/components/activities.html#StartingAnActivity.
Garey, M. R., Johnson, D. S. (1979). Computers and intractability: A guide to the theory of NP-completeness. In W. H. Freeman (Ed.).
Law, A. M., & Kelton, W. D. (1991). Simulation modeling and analysis (2nd ed.). New York: McGraw Hill Inc.
Glover, F. (1989). Tabu search—part I. ORSA Journal on Computing, 1(2), 190–206.
[Online]: http://voidexception.weebly.com/simple-tabu-search-using-java--traveling-sales-man-tsp.html.
Boloor, K., Chirkova, R., Salo, T., Viniotis, Y. (2010). Heuristic-based request scheduling subject to a percentile time SLA in a distributed cloud. In Proceedings of the IEEE Globecom 2010. Miami, USA.
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Liagouras, GA., Sayegh, A.A. & Koutsakis, P. A New Location-Aware Calendar-Based Application for Dynamic Minimum Path Trip Planning. Wireless Pers Commun 78, 29–44 (2014). https://doi.org/10.1007/s11277-014-1732-0
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DOI: https://doi.org/10.1007/s11277-014-1732-0