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Modélisation du contexte social : application aux réseaux opportunistes

Abstract : This thesis deals with the dynamic adaptation of context-aware applications using information related to the social environment of users to enrich the service rendered by the applications. To achieve this goal our contribution mobilizes multidimensional modeling of the different levels of social contexts, especially the weight of the relationship between the actors. Particularly, we synthesize not only social contexts related to familiarity but also social contexts reasoned from the similarity of static and dynamic communities. Two models based on respectively graphs and ontologies are proposed in order to satisfy the heterogeneity of the social networks in real life. We use the actual data gathered on online social networking services for conducting experiments and the results are analyzed by checking the effectiveness of the models. In parallel we consider the point of view of the application, and we present two algorithms using social contexts to improve the strategy of transmission of data in the opportunistic network, particularly countermeasure against selfish nodes. The simulations of real scenarios confirm the advantages of introducing social contexts in terms of success rate and delay of transmission. We carry out a comparison with other popular transmission algorithms in the literature
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Yaofu Cao. Modélisation du contexte social : application aux réseaux opportunistes. Sociologie. Université de Technologie de Troyes, 2017. Français. ⟨NNT : 2017TROY0002⟩. ⟨tel-02410058⟩

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