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Türkes, O. and Scholten, J. and Havinga, P.J.M. (2013) Introspection-based Periodicity Awareness Model for Intermittently Connected Mobile Networks. In: Proceedings of the Fourth International Conference on Mobile, Ubiquitous, and Intelligent Computing, MUSIC 2013, 4-6 Sep 2013, Gwangju, South Korea. pp. 397-403. Lecture Notes in Electrical Engineering (274). Springer Verlag. ISSN 1876-1100 ISBN 978-3-642-40675-1
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Official URL: http://dx.doi.org/10.1007/978-3-642-40675-1_61
Recently, context awareness in Intermittently Connected Mobile Networks (ICMNs) has gained popularity in order to discover social similarities among mobile entities. Nevertheless, most of the contextual methods depend on network knowledge obtained with unrealistic scenarios. Mobile entities should have a self-knowledge determination in order to estimate their activity routines in a group of communities. This paper presents a periodicity awareness model which relies on introspective spatiotemporal observations. In this model, hourly, daily, and weekly locations of mobile entities are being tracked to predict future trajectories and periodicities within a targeted time period. Realistic simulations are utilized to analyze the predictions in weekly observation sets. The results show that a reasonable accuracy with an increasing level of determination can be obtained which does not require global network knowledge. In this regard, the presented model can give insights for any type of ICMN objectives.
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