Context-based Grouping and Recommendation in MANETs

Yves Vanrompay 1 Manuele Kirsch Pinheiro 2 Nesrine Ben Mustapha 1 Marie-Aude Aufaure 1
1 MAS - Mathématiques Appliquées aux Systèmes - EA 4037
2 CRI - Centre de Recherche en Informatique
Abstract : We propose in this chapter a context grouping mechanism for context distribution over MANETs. Context distribution is becoming a key aspect for successful context-aware applications in mobile and ubiquitous computing environments. Such applications need, for adaptation purposes, context information that is acquired by multiple context sensors distributed over the environment. Nevertheless, applications are not interested in all available context information. Context distribution mechanisms have to cope with the dynamicity that characterizes MANETs and also prevent context information to be delivered to nodes (and applications) that are not interested in it. Our grouping mechanism organizes the distribution of context information in groups whose definition is context based: each context group is defined based on a criteria set (e.g. the shared location and interest) and has a dissemination set, which controls the information that can be shared in the group. We propose a personalized and dynamic way of defining and joining groups by providing a lattice-based classification and recommendation mechanism that analyzes the interrelations between groups and users, and recommend new groups to users, based on the interests and preferences of the user.
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Chapitre d'ouvrage
Kostas Kolomvatsos, Christos Anagnostopoulos, Stathes Hadjiefthymiades. Intelligent Technologies and Techniques for Pervasive Computing, IGI Global, pp.157-178, 2013
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Soumis le : vendredi 7 juin 2013 - 15:10:02
Dernière modification le : lundi 12 novembre 2018 - 10:57:24
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Yves Vanrompay, Manuele Kirsch Pinheiro, Nesrine Ben Mustapha, Marie-Aude Aufaure. Context-based Grouping and Recommendation in MANETs. Kostas Kolomvatsos, Christos Anagnostopoulos, Stathes Hadjiefthymiades. Intelligent Technologies and Techniques for Pervasive Computing, IGI Global, pp.157-178, 2013. 〈hal-00831704〉

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