{"id":841,"date":"2017-02-09T21:42:00","date_gmt":"2017-02-09T20:42:00","guid":{"rendered":"https:\/\/samovar2022.int-evry.fr\/index.php\/2017\/02\/09\/analyse-et-influence-des-parametres-daffaires-sur-la-qualite-dexperience-des-services-over-the-top\/"},"modified":"2020-09-04T18:46:10","modified_gmt":"2020-09-04T16:46:10","slug":"analyse-et-influence-des-parametres-daffaires-sur-la-qualite-dexperience-des-services-over-the-top","status":"publish","type":"post","link":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/2017\/02\/09\/analyse-et-influence-des-parametres-daffaires-sur-la-qualite-dexperience-des-services-over-the-top\/","title":{"rendered":"\u00ab Analyse et influence des param\u00e8tres d\u2019affaires sur la qualit\u00e9 d\u2019exp\u00e9rience des services Over-The-Top \u00bb"},"content":{"rendered":"<p>L&rsquo;Ecole doctorale : Sciences et Technologies de l&rsquo;Information et de la Communication avec T\u00e9l\u00e9com SudParis et le Laboratoire de recherche SAMOVAR<br \/>\npr\u00e9sentent<br \/>\nl\u2019AVIS DE SOUTENANCE de <strong>Monsieur Diego RIVERA<\/strong><br \/>\nAutoris\u00e9 \u00e0 pr\u00e9senter ses travaux en vue de l\u2019obtention du Doctorat de l&rsquo;Universit\u00e9 Paris-Saclay, pr\u00e9par\u00e9 \u00e0 T\u00e9l\u00e9com SudParis en :<br \/>\nr\u00e9seaux, information et communications<\/p>\n<p>\n<strong>Quand: <\/strong> le mardi 28 f\u00e9vrier 2017 \u00e0 15h00<\/p>\n<p><strong>Ou: <\/strong> \u00e0 T\u00e9l\u00e9com SudParis &#8211; Salle A003 &#8211; 9 rue Charles Fourier 91011 Evry<\/p>\n<p><strong>Membres du jury :<\/strong><\/p>\n<table>\n<tbody>\n<tr class='row_even'>\n<td>Mme Ana Rosa CAVALLI<\/td>\n<td>Professeur \u00e9m\u00e9rite, T\u00e9l\u00e9com SudParis, FRANCE <\/td>\n<td>Directrice de th\u00e8se<\/td>\n<\/tr>\n<tr class='row_odd'>\n<td>M. S\u00e9bastien TIXEUIL<\/td>\n<td> Professeur, Universit\u00e9 Pierre et Marie Curie &#8211; Paris 6, FRANCE<\/td>\n<td>Rapporteur<\/td>\n<\/tr>\n<tr class='row_even'>\n<td>M. Patrick SENAC<\/td>\n<td> Professeur, Ecole Nationale de l&rsquo;Aviation Civile, FRANCE<\/td>\n<td>Rapporteur<\/td>\n<\/tr>\n<tr class='row_odd'>\n<td>M. Fr\u00e9d\u00e9ric CUPPENS<\/td>\n<td> Professeur, IMT Atlantique, FRANCE <\/td>\n<td> Examinateur<\/td>\n<\/tr>\n<tr class='row_even'>\n<td>M. Abdelhamid MELLOUK<\/td>\n<td> Professeur, Universit\u00e9 Paris-Est, FRANCE<\/td>\n<td> Examinateur<\/td>\n<\/tr>\n<tr class='row_odd'>\n<td>Mme Natalia KUSHIK<\/td>\n<td>Ma\u00eetre de conf\u00e9rences, T\u00e9l\u00e9com SudParis, FRANCE<\/td>\n<td>Examinateur<\/td>\n<\/tr>\n<tr class='row_even'>\n<td>Mme Fatiha ZAIDI<\/td>\n<td> Ma\u00eetre de conf\u00e9rences, Universit\u00e9 Paris Sud, FRANCE <\/td>\n<td>Examinateur<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><em>R\u00e9sum\u00e9 :<\/em><\/p>\n<p>A l&rsquo;\u00e9poque o\u00f9 l&rsquo;Internet est devenu la plateforme par d\u00e9faut pour offrir de la valeur ajout\u00e9e, des nouveaux fournisseurs de services multim\u00e9dia ont saisi cette opportunit\u00e9 en d\u00e9finissant les services Over-The-Top (OTT). Cependant, Internet n&rsquo;\u00e9tant pas un r\u00e9seau de distribution fiable, il n\u00e9cessaire de garantir de haut niveau de Qualit\u00e9 d&rsquo;Exp\u00e9rience (QoE), ainsi que les revenues des Fournisseurs de Services d&rsquo;Internet (ISP) et des OTTs. Le travail pr\u00e9sent\u00e9 dans ce document va au-del\u00e0 de l&rsquo;\u00e9tat de l&rsquo;art, en proposant une solution qui prend en compte cet objectif. Les principaux apports qui y sont pr\u00e9sent\u00e9s peuvent \u00eatre synth\u00e9tis\u00e9es en quatre contributions. En premier lieu, l&rsquo;inclusion des param\u00e8tres li\u00e9s aux mod\u00e8les d&rsquo;affaires dans l&rsquo;analyse de la QoE a demand\u00e9 un nouveau cadre pour calculer la QoE d&rsquo;un service OTT. Ce cadre est bas\u00e9 sur le formalisme math\u00e9matique des Machines \u00c9tendues \u00e0 \u00c9tats Finis (EFSM), ce qui profite de deux avantages des EFSMs~: les traces des machines suivent les d\u00e9cisions de l&rsquo;utilisateur et les variables du contexte utilis\u00e9s comme indicateurs de qualit\u00e9, seront utilis\u00e9es ult\u00e9rieurement pour computer la QoE. La deuxi\u00e8me contribution consiste \u00e0 mettre en \u0153uvre deux algorithmes. Le premier fait le calcul d&rsquo;une forme \u00e9quivalent, ayant la forme d&rsquo;un arbre qui repr\u00e9sente les traces de la machine. Le deuxi\u00e8me utilise les traces et fait le calcul de la QoE pour les \u00e9tats terminaux de chaque trace. Les deux algorithmes peuvent \u00eatre utilis\u00e9s comme base d&rsquo;un outil de monitorage capable de pr\u00e9voir la valeur de la QoE d&rsquo;un utilisateur. De plus, une mise en \u0153uvre concr\u00e8te des ces deux algorithmes comme une extension de l&rsquo;Outil de Monitorage de Montimage (MMT) est aussi pr\u00e9sent\u00e9e. La troisi\u00e8me contribution pr\u00e9sente la validation de l&rsquo;approche avec un double objectif. D&rsquo;une part, l&rsquo;inclusion de param\u00e8tres du mod\u00e8le d&rsquo;affaires est valid\u00e9e et on d\u00e9termine leur impact sur la QoE. D&rsquo;autre part, le mod\u00e8le de la QoE propos\u00e9 est valid\u00e9 par la mise en \u0153uvre d&rsquo;une plateforme d&rsquo;\u00e9mulation d&rsquo;un service OTT qui montre des vid\u00e9os perturb\u00e9s. Cette impl\u00e9mentation est utilis\u00e9e pour obtenir des valeurs estim\u00e9es par utilisateurs r\u00e9els qui sont utilis\u00e9s pour d\u00e9river un mod\u00e8le appropri\u00e9 de la QoE. La derni\u00e8re contribution se base sur le cadre donn\u00e9 et fournit un analyse statique d&rsquo;un service OTT. Cette proc\u00e9dure est r\u00e9alis\u00e9 par un troisi\u00e8me algorithme qui calcule la quantit\u00e9 des configurations contenues dans le mod\u00e8le. En analysant \u00e0 l&rsquo;avance touts les sc\u00e9narios possibles qu&rsquo;un utilisateur peut rencontrer, le fournisseur des services OTT peut d\u00e9tecter des d\u00e9fauts dans le mod\u00e8le et le service \u00e0 une stade pr\u00e9coce du d\u00e9veloppement.<\/p>\n<p><em>Abstract :<\/em><\/p>\n<p>At a time when the Internet has become the de facto platform for delivering value, the new multimedia providers took advantage of this opportunity to define Over-The-Top (OTT) services. Considering that Internet is not a reliable distribution network, it is necessary to ensure high levels of Quality of Experience (QoE) and revenues for Internet Service Providers (ISP) and OTTs. The work presented in this dissertation goes beyond the state of the art by providing a solution having this goal in mind. The main contributions presented here can be summarized in four main points. First, the inclusion of business-model related parameters in the QoE analysis required a new framework for calculating the QoE of an OTT service. This framework is based on the Extended Finite States Machine (EFSM) mathematical formalism, which takes advantage of two features of the EFSMs: (1) the traces of the machines that keep track of the user&rsquo;s decisions and; (2) the context variables used as quality indicators, correlated later with the QoE. The second contribution is the design and the implementation of two algorithms. The first computes the $l$-equivalent, a version in the form of a tree of the model that exposes the traces of the machine. The second uses the traces and computes the QoE at the final stages of each trace. Both algorithms can be used to design a monitoring tool that can predict a user\u2019s QoE value. In addition, a concrete implementation is given as an extension of the Montimage Monitoring Tool (MMT). The third contribution presents the validation of the approach, having two objectives in mind. On the one hand, the inclusion of business-model related parameters was validated by determining the impact of such variables on the QoE. On the other hand, the proposed QoE model is validated by the implementation of an OTT emulation platform showing disrupted videos. This implementation is used to obtain QoE values evaluated from real users, values used to derive an appropriate QoE model. The last contribution uses the framework to perform a static analysis of an OTT service. This is done by a third algorithm that computes the amount of configurations contained in the model. By analyzing in advance all the possible scenarios a user can face &#8212; and their respective QoE, the OTT provider can detect flaws in the model and the service from the early stages of development.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>L&rsquo;Ecole doctorale : Sciences et Technologies de l&rsquo;Information et de la Communication avec T\u00e9l\u00e9com SudParis et le Laboratoire de recherche SAMOVAR pr\u00e9sentent l\u2019AVIS DE SOUTENANCE de Monsieur Diego RIVERA Autoris\u00e9 \u00e0 pr\u00e9senter ses travaux en vue de l\u2019obtention du Doctorat de l&rsquo;Universit\u00e9 Paris-Saclay, pr\u00e9par\u00e9 \u00e0 T\u00e9l\u00e9com SudParis en : r\u00e9seaux, information et communications Quand: le 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