{"id":367,"date":"2012-09-13T13:36:08","date_gmt":"2012-09-13T11:36:08","guid":{"rendered":"https:\/\/samovar2022.int-evry.fr\/index.php\/2012\/09\/13\/soutenance-these-de-mohamed-haykel-zayani\/"},"modified":"2020-09-04T18:46:58","modified_gmt":"2020-09-04T16:46:58","slug":"soutenance-these-de-mohamed-haykel-zayani","status":"publish","type":"post","link":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/2012\/09\/13\/soutenance-these-de-mohamed-haykel-zayani\/","title":{"rendered":"Soutenance : Th\u00e8se de Mohamed-Haykel Zayani"},"content":{"rendered":"

20 septembre<\/strong> 2012, \u00e0 la salle A001<\/strong> \u00e0 partir de 10<\/strong>h00<\/p>\n

\u00ab\u00a0La Pr\u00e9diction de Liens dans les R\u00e9seaux Sans-fil Mobiles et Dynamiques Centr\u00e9s sur l\u2019\u00catre Humain\u00a0\u00bb.<\/strong><\/p>\n

Cette th\u00e8se a \u00e9t\u00e9 supervis\u00e9e et encadr\u00e9e par Professeur Djamal ZEGHLACHE et Docteur Vincent GAUTHIER de l’Institut Mines-TELECOM SudParis (laboratoire SAMOVAR) et par Professeur Sami TABBANE et Docteur Houda KHEDHER de l’Institut Sup\u00e9rieur des T\u00e9l\u00e9communications (SUP’COM) de Tunis.<\/p>\n

– Mme Hassnaa MOUTAFA – Rapporteur – Ing\u00e9nieur de Recherche S\u00e9nior, Orange Labs
\n– M. Andr\u00e9-Luc BEYLOT \tRapporteur \tProfesseur, IRIT\/ENSEEIHT
\n– M. Marcelo DIAS de AMORIM – Examinateur – Charg\u00e9 de Recherche, LIP6\/CNRS
\n– Mme Pascale MINET – Examinateur – Chercheur HDR, INRIA Recquencourt
\n– M. Farid BENBADIS – Examinateur – Ing\u00e9nieur Chercheur, Thal\u00e8s Communications
\n– M. Djamal ZEGHLACHE – Directeur de th\u00e8se – Professeur, TELECOM SudParis
\n– M. Sami TABBANE – Co-directeur de th\u00e8se – Professeur, SUP’COM Tunis
\n– M. Vincent GAUTHIER – Encadrant – Ma\u00eetre de Conf\u00e9rences, TELECOM SudParis<\/p>\n

R\u00e9sum\u00e9:<\/strong><\/p>\n

Durant ces derni\u00e8res ann\u00e9es, nous avons observe une expansion progressive et continue des r\u00e9seaux mobile sans-fil centres sur l\u2019\u00eatre humain. L\u2019apparition de ces r\u00e9seaux a encourag\u00e9 les chercheurs \u00e0 r\u00e9fl\u00e9chir \u00e0 de nouvelles solutions pour assurer une \u00e9valuation efficace et une conception ad\u00e9quate des protocoles de communication. En effet, ces r\u00e9seaux sont sujets \u00e0 de multiples contraintes telles que le manque d\u2019infrastructure, la topologie dynamique, les ressources limit\u00e9es ainsi que la qualit\u00e9 de service et la s\u00e9curit\u00e9 des informations pr\u00e9caires. Nous nous sommes sp\u00e9cialement int\u00e9ress\u00e9s \u00e0 l\u2019aspect dynamique du r\u00e9seau et en particulier \u00e0 la mobilit\u00e9 humaine. La mobilit\u00e9 humaine a \u00e9t\u00e9 largement \u00e9tudi\u00e9e pour pouvoir extraire ses propri\u00e9t\u00e9s intrins\u00e8ques et les exploiter pour des approches plus adapt\u00e9es \u00e0 cette mobilit\u00e9. Parmi les propri\u00e9t\u00e9s les plus int\u00e9ressantes soulev\u00e9es dans la litt\u00e9rature, nous nous sommes focalis\u00e9s sur l\u2019impact des interactions sociales entre les entit\u00e9s du r\u00e9seau sur la mobilit\u00e9 humaine et en cons\u00e9quence sur la structure du r\u00e9seau. Pour recueillir des informations structurelles sur le r\u00e9seau, plusieurs m\u00e9triques et techniques ont \u00e9t\u00e9 emprunt\u00e9es de l\u2019analyse des r\u00e9seaux sociaux (Social Network Analysis not\u00e9e \u00e9galement SNA). Cet outil peut \u00eatre assimil\u00e9 \u00e0 une autre alternative pour mesurer des indicateurs de performance du r\u00e9seau. Plus pr\u00e9cis\u00e9ment, il extrait des informations structurelles du r\u00e9seau et permet aux protocoles de communication de b\u00e9n\u00e9ficier d\u2019indications utiles telles que la robustesse du r\u00e9seau, les n\u0153uds centraux ou encore les communaut\u00e9s \u00e9mergentes. Dans ce contexte, la SNA a \u00e9t\u00e9 largement utilis\u00e9e pour pr\u00e9dire les liens dans les r\u00e9seaux sociaux en se basant notamment sur les informations structurelles.<\/p>\n

Motiv\u00e9s par l\u2019importance des liens sociaux dans les r\u00e9seaux mobiles sans-fil centres sur l\u2019\u00eatre humain et par les possibilit\u00e9s offertes par la SNA pour pr\u00e9dire les liens, nous nous proposons de concevoir la premi\u00e8re m\u00e9thode capable de pr\u00e9dire les liens dans les r\u00e9seaux sans-fil mobiles tels que les r\u00e9seaux ad-hoc mobiles (Mobile Ad-Hoc Networks ou MANETs) et les r\u00e9seaux tol\u00e9rants aux d\u00e9lais (Delay\/Disruption Tolerant Networks ou DTNs). Notre proposition suit l\u2019\u00e9volution de la topologie du r\u00e9seau sur T p\u00e9riodes \u00e0 travers un tenseur (en ensemble de matrices d\u2019adjacence et chacune des matrices correspond aux contacts observ\u00e9s durant une p\u00e9riode bien sp\u00e9cifique). Ensuite, elle s\u2019appuie sur le calcul de la mesure sociom\u00e9trique de Katz pour chaque paire de n\u0153uds pour mesurer l\u2019\u00e9tendue des relations sociales entre les diff\u00e9rentes entit\u00e9s du r\u00e9seau. Une telle quantification donne un aper\u00e7u sur les liens dont l\u2019occurrence est fortement pressentie \u00e0 la p\u00e9riode T+1 et les nouveaux liens qui se cr\u00e9ent dans le futur sans pour autant avoir \u00e9t\u00e9 observ\u00e9s durant le temps de suivi. Pour attester l\u2019efficacit\u00e9 de notre proposition, nous l\u2019appliquons sur trois traces r\u00e9elles et nous comparons sa performance \u00e0 celles d\u2019autres techniques de pr\u00e9diction de liens pr\u00e9sent\u00e9es dans la litt\u00e9rature. Les r\u00e9sultats prouvent que notre m\u00e9thode est capable d\u2019atteindre le meilleur niveau d\u2019efficacit\u00e9 et sa performance surpasse celles des autres techniques. L\u2019une des majeures contributions apport\u00e9es par cette proposition met en exergue la possibilit\u00e9 de pr\u00e9dire les liens d\u2019une mani\u00e8re d\u00e9centralis\u00e9e. En d\u2019autres termes, les n\u0153uds sont capables de pr\u00e9dire leurs propres liens dans le futur en se basant seulement sur la connaissance du voisinage imm\u00e9diat (voisins \u00e0 un et deux sauts).<\/p>\n

En outre, nous sommes d\u00e9sireux d\u2019am\u00e9liorer encore plus la performance de notre m\u00e9thode de pr\u00e9diction de liens. Pour quantifier la force des relations sociales entre les entit\u00e9s du r\u00e9seau, nous consid\u00e9rons deux aspects dans les relations : la r\u00e9cence des interactions et leur fr\u00e9quence. \u00c0 partir de l\u00e0, nous nous demandons s\u2019il est possible de prendre en compte un troisi\u00e8me crit\u00e8re pour am\u00e9liorer la pr\u00e9cision des pr\u00e9dictions. En soutenant l\u2019heuristique qui stipule que les liens persistants sont fortement pr\u00e9dictibles, nous consid\u00e9rons la stabilit\u00e9 des relations (lien ou proximit\u00e9 \u00e0 deux sauts). Pour mesurer cette stabilit\u00e9, nous optons pour l\u2019estimation d\u2019entropie d\u2019un ph\u00e9nom\u00e8ne \u00e9voluant dans le temps propos\u00e9e dans l\u2019algorithme de compression de Lempel-Ziv. Nous consid\u00e9rons que les mesures fournies par notre m\u00e9thode et les mesures de stabilit\u00e9 se compl\u00e8tent et nous proposons en cons\u00e9quence diff\u00e9rentes combinaisons pour la conception de nouvelles m\u00e9triques de pr\u00e9diction de liens. Les r\u00e9sultats de simulation confirment le fondement de notre intuition.<\/p>\n

La proposition d\u2019une m\u00e9thode de pr\u00e9diction de liens bas\u00e9e sur les tenseurs et la d\u00e9rivation de nouvelles m\u00e9triques li\u00e9es \u00e0 la stabilit\u00e9 des relations pour l\u2019am\u00e9lioration de cette m\u00e9thode repr\u00e9sentent les contributions majeures de cette th\u00e8se. Le long de cette th\u00e8se, notre souci a \u00e9t\u00e9 de r\u00e9fl\u00e9chir sur des m\u00e9canismes et des m\u00e9triques capables d\u2019am\u00e9liorer l\u2019\u00e9valuation ou la conception des protocoles de communication. N\u00e9anmoins, nos efforts ne ce sont pas limit\u00e9s aux travaux de pr\u00e9diction de liens et nous avons eu l\u2019opportunit\u00e9 de proposer deux autres contributions. D\u2019une part, nous proposons un mod\u00e8le commun pour les couches physique et liaison de donn\u00e9es pour le standard IEEE 802.15.4. D\u2019autre part, nous avan\u00e7ons un m\u00e9canisme d\u2019apprentissage bas\u00e9 sur un jeu r\u00e9p\u00e9titif, inspir\u00e9 du c\u00e9l\u00e8bre jeu t\u00e9l\u00e9vis\u00e9 \u00ab Le Maillon Faible \u00bb, pour stimuler la coop\u00e9ration dans un r\u00e9seau ad-hoc non coop\u00e9ratif.
\nMots-Cl\u00e9s : R\u00e9seau sans-fil mobile centr\u00e9s sur l\u2019\u00eatre humain, pr\u00e9diction de liens, tenseur, liens sociaux, mesure de Katz, stabilit\u00e9s de lien et de proximit\u00e9, entropie.<\/p>\n

Abstract:<\/strong><\/p>\n

During the last years, we have observed a progressive and continuous expansion of human-centered mobile wireless networks. The advent of these networks has encouraged the researchers to think about new solutions in order to ensure efficient evaluation and design of communication protocols. In fact, these networks are faced to several constraints as the lack of infrastructure, the dynamic topology, the limited resources and the deficient quality of service and security. We have been interested in the dynamicity of the network and in particular in human mobility. The human mobility has been widely studied in order to extract its intrinsic properties and to harness them to propose more accurate approaches. Among the prominent properties depicted in the literature, we have been specially attracted by the impact of the social interactions on the human mobility and consequently on the structure of the network. To grasp structural information of such networks, many metrics and techniques have been borrowed from the Social Network Analysis (SNA). The SNA can be seen as another network measurement task which extracts structural information of the network and provides useful feedback for communication protocols. In this context, the SNA has been extensively used to perform link prediction in social networks relying on their structural properties.<\/p>\n

Motivated by the importance of social ties in human-centered mobile wireless networks and by the possibilities that are brought by SNA to perform link prediction, we are interested by designing the first link prediction framework adapted for mobile wireless networks as Mobile Ad-hoc Networks (MANETs) and Delay\/Disruption Tolerant Networks (DTN). Our proposal tracks the evolution of the network through a third-order tensor over T periods and computes the sociometric Katz measure for each pair of nodes to quantify the strength of the social ties between the network entities. Such quantification gives insights about the links that are expected to occur in the period T+1 and the new links that are created in the future without being observed during the tracking time. To attest the efficiency of our framework, we apply our link prediction technique on three real traces and we compare its performance to the ones of other well-known link prediction approaches. The results prove that our method reaches the highest level of accuracy and outperforms the other techniques. One of the major contributions behind our proposal highlights that the link prediction in such networks can be made in a distributed way. In other words, the nodes can predict their future links relying on the local information (one-hop and two-hop neighbors) instead of a full knowledge about the topology of the network.<\/p>\n

Furthermore, we are keen to improve the link prediction performance of our tensor-based framework. To quantify the social closeness between the users, we take into consideration two aspects of the relationships: the recentness of the interactions and their frequency. From this perspective, we wonder if we can consider a third criterion to improve the link prediction precision. Asserting the heuristic that stipulates that persistent links are highly predictable, we take into account the stability of the relationships (link and proximity stabilities). To measure it, we opt for the entropy estimation of a time series proposed in the Lempel-Ziv data compression algorithm. As we think that our framework measurements and the stability estimations complement each other, we combine them in order to provide new link prediction metrics. The simulation results emphasize the pertinence of our intuition.<\/p>\n

Providing a tensor-based link prediction framework and proposing relative enhancements tied to stability considerations represent the main contributions of this thesis. Along the thesis, our concern was also focused on mechanisms and metrics that contribute towards improving communication protocols in these mobile networks. Nevertheless, our efforts were not limited to the major contributions previously mentioned and we had the opportunity to
\npropose two other approaches that can be useful to improve the design and the evaluation of protocols in mobile multi-hop networks. Firstly, we propose a joint model for the IEEE 802.15.4 physical and medium access control layers. Secondly, we advance a self-learning repeated game framework, inspired by \u00ab\u00a0The Weakest Link\u00a0\u00bb TV game, to enforce cooperation in non-cooperative ad-hoc networks.<\/p>\n

Keywords: Human-centered mobile wireless networks, link prediction, tensor, social ties, Katz measure, link and proximity stabilities, entropy.<\/p>\n

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20 septembre 2012, \u00e0 la salle A001 \u00e0 partir de 10h00 \u00ab\u00a0La Pr\u00e9diction de Liens dans les R\u00e9seaux Sans-fil Mobiles et Dynamiques Centr\u00e9s sur l\u2019\u00catre Humain\u00a0\u00bb. Cette th\u00e8se a \u00e9t\u00e9 supervis\u00e9e et encadr\u00e9e par Professeur Djamal ZEGHLACHE et Docteur Vincent GAUTHIER de l’Institut Mines-TELECOM SudParis (laboratoire SAMOVAR) et par Professeur Sami TABBANE et Docteur Houda 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