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Modèles probabilistes et statistiques pour la conception et l'analyse des systèmes de communications

Abstract : Two different problems are addressed in this thesis : traffic prediction and classification and access mechanisms in MANETS. In the first part of the thesis, we address the problem of traffic prediction and classsification by means of advanced statistical tools. We analyze the problem of online prediction of the load on a link based only on past measurements and without assuming any particular model. Concerning traffic classification, and motivated by the widespread use of P2P systems, we focus on the identification of P2P applications, considering more precisely the case of P2P television (P2P-TV). For both cases, our framework makes use of Support Vector Machines (SVM). The algorithms we propose provide very accurate results, they are robust and their computational cost is extremely low. These properties make our solutions specially adapted to an online application. Self-organized systems such as MANETs, are of particular importance in today's world. In the second part of the thesis, we address two different problems related to MAC mechanisms in MANETs (in particular, we concentrate on CSMA). Firstly, an analysis of the existing models for CSMA, with special emphasis on their correlation with the real protocol, is presented. Some weakness are identified and possible solutions are proposed. The use of stochastic geometry tools allows us to obtain analytical results where other techniques cannot. Secondly, we address the problem of lack of QoS in CSMA and we propose two different mechanisms that guarantee a minimum rate for each accepted transmission. The main aim of our study is to identify which of the proposed mechanisms outperforms CSMA best depending on the scenario.
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Submitted on : Monday, March 8, 2010 - 8:00:00 AM
Last modification on : Friday, July 31, 2020 - 10:44:07 AM
Long-term archiving on: : Thursday, March 30, 2017 - 5:12:17 AM


  • HAL Id : pastel-00005853, version 1


Paola Bermolen. Modèles probabilistes et statistiques pour la conception et l'analyse des systèmes de communications. domain_other. Télécom ParisTech, 2010. Français. ⟨pastel-00005853⟩



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