Analysis and control of diffusion processes in networks

Abstract : The propagation of a characteristic through a network is the subject of study of many scientific fields. Epidemics, viral marketing or information propagation through a social network are among the many examples of real phenomena modeled by the evolution of a characteristic propagating through the edges of a network. Thus, being capable of acting on these diffusion processes is of capital interest for many fields. Despite the large literature about the theoretical aspects of diffusion processes, and more specifically the discovery of an epidemic threshold under which the propagation is not sustainable, a number of practical limitations prevent the use of these studies in real-life scenarios. In this thesis, we work on reducing the distance separating theory from practice, following three distinct research directions: the generalization of theoretical results to a larger, and more realistic, class of diffusion models, the development of efficient dynamic control measures utilizing the structure of network to its advantage, and, finally, the definition of new mathematical tools bridging the gap between spatial and network approaches in epidemiology. More specifically, our work allows the rigorous analysis of the behavior of a network's characteristics when it converges, in a structural sense, to a given metric space, and could open the way to the application of control strategies on networks to spatial and macroscopic information (e.g. transportation or demographic data) about the contact network in a given population.
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Kevin Scaman. Analysis and control of diffusion processes in networks. General Mathematics [math.GM]. Université Paris-Saclay, 2016. English. ⟨NNT : 2016SACLN039⟩. ⟨tel-01531840⟩

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