N° d’ordre : 2774
THÈSE DE DOCTORAT
Présentée parSihame EL-HAMMANI
Discipline : Science de l’ingénieur
Spécialité : Informatique et Télécommunications
Advances in Wireless and Mobile Communication Networks: A
Multi-Layer Analysis
Soutenue publiquement le 09 Juin 2015:
Devant le jury Président :
M. BOUYAKHF El-Houssine Professeur, FSR, Rabat
Examinateurs :
M. HAQIQ Abdelkrim Professeur, FSTS, Settat M. KOBBANE Abdellatif Professeur habilité, ENSIAS, Rabat M. HIMMI Mohammed Majid Professeur, FSR, Rabat M. EL-KAMILI Mohamed Professeur habilité, FSDM, Fès M. IBRAHIMI Khalil Professeur habilité, FSK, Kenitra
UNIVERSITÉ MOHAMMED V
FACULTÉ DES SCIENCES
Acknowledgments
I would like to express my special appreciation and thanks to my advisor Prof. El Houssine BOUYAKHF (Professor at Faculty of Science Rabat and laboratory director) for all the support, guidance, generosity, patience and encouragement that he has given me during the course of my research . Without his radiological insight, experience and support, the study of this thesis would have been difficult or impossible to carry out. Thanks for your patience and dedication to the research. It has been an absolute pleasure to have worked with you. Thank you also for agreeing to be president of the jury members.
I wish to express my deep gratitude to my co-advisors Prof. Khalil IBRAHIMI (Professor at Faculty of Science kenitra) for the enriching discussions,assistance, en-couragement and extremely useful feedback. The valuable discussions with you have always been very enlightening for me, and have helped me immensely in developing the ideas presented in this thesis. Thank you also for having accepted to be among the jury members.
I sincerely thank my reviewer Prof. Abdelkrim HAQIQ (Professor at the faculty of Science and Technology, Settat) who agreed to judge this work and to participate in the jury. Thank you for providing insightful and helpful feedback.
I am profoundly thankful to my reviewer Prof. Abdellatif KOBBANE (Professor at Superior National School of Computer and Systems Analysis) your comments and opinions have helped me to clarify and improve the quality of my manuscript. Thank you also for having accepted to be among the jury members.
I am grateful to Prof. Mohammed Majid HIMMI (Professor at the faculty of science, Rabat) to be among the jury members. Thank you for your brilliant comments and suggestions.
My sincere thanks go to Prof. Mohamed EL-Kamlili (Professor at Dhar El Mahraz faculty of science, University Sidi Mohamed Ben Abdellah, Fez) who agreed to evaluate my thesis and participate in the jury.
I extend my gratitude and appreciation to those who have contributed to the im-provement and the reviewing of the manuscript. Whatever I do, I can not thank you enough. In particular, I think to Prof. Mohamed BASLAM, Prof. Essaid SABIR and Ms. Soufiana MEKOUAR.
I am so grateful to all past and present colleagues at LIMIARF and to all my friends (too many to list them but you know who you are!) for the joyful and pleasant working environment, and for providing support and friendship that I needed.
Most importantly, my deepest gratitude also goes to my parents Khadija EL-HAJJAJI EL-IDRISSI and Abderrahmane EL-HAMMANI who have always filled my life with generous love, and unconditional support. This doctorate is truly theirs! My thanks go also to my husband Abdellatif TOUBATI and all my family for their endless moral support throughout my career. Without you, I will not reach this academic degree. To them I dedicate this thesis.
Rabat, June 09, 2015
Abstract
Keywords: WiMAX; Femtocells; Slotted Aloha; Social Network; Game Theory; Learn-ing Algorithms; TCP/IP Architecture; Performances Evaluation.
The aim of this thesis is to provide the reader with a comprehensive view of the ad-vances in wireless and mobile communication networks, while adopting a multi-layer analysis. We rely on a TCP/IP architecture, and by browsing layers we try to cover dif-ferent aspects of analysis, design, and optimization problems for heterogeneous wireless networks. We are more particularly interested in the physic, link and application layers that are very important, play a major role and have a great influence in the system per-formances.
In the physical layer, we study and analyse the performance of two new technologies. Firstly, the wireless metropolitan area network (MAN) illustrated in WiMAX technol-ogy. And secondly, femtocell technology as special class of small cells, that can cover small areas with low power transmission which has become increasingly important for the indoor areas. Furthermore, as the choice of medium access control (MAC) protocol can affect the system performance and the use of wireless networks, we investigate one of the most popular random accesses MAC protocols, illustrated on slotted aloha pro-tocol that affects directly the interoperability and the global roaming of mobile users. And finally, we focus on a practical case in the application layer by addressing the min-imization of content diffusion time problem in social networks.
Résumé
Mots clés : WiMAX; Femtocells; Slotted Aloha; Réseaux Sociaux; Théorie des jeux; Algorithmes d’apprentissage; Architecture TCP/IP; Évaluation des Performances. L’objectif de cette thèse est de fournir une vue d’ensemble des progrès réalisés dans les réseaux de communication sans fil et mobiles, tout en adoptant une analyse mul-ticouche. Nous nous basons sur l’architecture TCP/IP, et en parcourant les couches de ce modèle, nous essayons de couvrir différents aspects d’analyse, de conception, et d’optimisation des problèmes dans les réseaux sans fil hétérogènes. Nous sommes plus particulièrement intéressé aux couches physique, liaison de donnée et application qui jouent un rôle majeur et ont une grande influence sur les performances du système. Dans la couche physique, nous étudions et analysons les performances de deux nou-velles technologies. Tout d’abord, le réseau métropolitain sans fil (MAN) illustré dans la technologie WiMAX. Et après, les petites cellules, et comme cas spéciale les femto-cellules, qui peuvent couvrir des petites zones à faible puissance de transmission et qui sont devenu de plus en plus important pour les espaces intérieurs. En outre, et comme le choix du protocole de contrôle d’accès au médium (MAC) influence beau-coup la performance du système, nous étudions l’un des plus populaires protocoles MAC d’accès multiple aléatoire, illustrés dans le protocole Slotted Aloha qui affecte directement l’interopérabilité et le roaming global des utilisateurs mobiles. Et enfin, nous nous concentrons sur un cas pratique dans la couche d’application en abordant le problème de la minimisation du temps de diffusion des contenus dans les réseaux sociaux.
Résumé Détaillé
Les réseaux sans fil ont connu un développement important durant ces dernières an-nées. Leur utilisation dans notre vie quotidienne a augmenté et dans un proche avenir, ces réseaux seront intégrés dans de nombreux nouveaux domaines et applications. En outre, une multitude de réseaux de communication sans fil sera basée sur une variété des technologies d’accès radio plus développée et s’appuiera sur de nouvelles normes qui doivent émerger et coexister.
L’utilisation de réseaux sans fil à la place de réseaux câblés ouvre de nouveaux défis de la recherche. Ces défis comprennent la mobilité, la qualité de service, la gestion de ressources et les aspects de la sécurité et de la confidentialité. Dans cette thèse, certains aspects de différents réseaux sans fil seront étudiées.
Les travaux de ce manuscrit peuvent être classés selon certaines couches du modèle TCP/IP : la couche application, la couche MAC et la couche physique. Nous nous focalisons sur une analyse des performances et une étude des problèmes d’optimisation de certaines technologies liées à ces couches. Nous nous basons dans nos analyses sur plusieurs techniques et outils qui sont bien connus et qui ont montré leurs efficacités à plusieurs reprises. Plus précisément, nous adoptons dans la majorité des travaux de cette thèse, une modélisation des problèmes en utilisant le concept de la théorie des jeux et nous optimisons les résultats via des outils d’apprentissage par renforcement.
Au cours de cette thèse, nous sommes intéressé à traiter plusieurs problématiques relatives à divers technologies. Et nous avons essayé de tirer les points faibles et les défis qui ne sont pas bien couverts dans la littérature. Ceci nous a permis aussi de dessiner la feuille de route pour la suite de nos travaux de recherche.
Dans cette thèse, nous proposons une analyse multi-couches des réseaux mobiles et sans fil. Nous nous intéressons en particulier, aux problèmes relatifs au contrôle d’admission centralisé des appels avec contraintes du temps réel. Aussi, nous essayons d’améliorer
ce contrôle via les cellules femtos afin de décharger le trafic du réseau et garantir une bonne qualité de service aux utilisateurs. Également, dans ce manuscrit, nous traitons le problème de gestion du contrôle d’accès au médium et nous exploitons les réseaux sociaux.
Tout d’abord, nous considérons le cas des grandes cellules. Nous choisissons une cellule OFDMA basée sur la technologie WiMAX, IEEE 802.16e. Et nous proposons un système d’allocation de ressources et de gestion de la mobilité en présence d’un trafic en temps réel.
Par la suite, nous proposons d’étudier le cas des petites cellules qui offrent une approche intéressante aux problèmes du qualité de services dans les grandes cellules. En effet, la zone de couverture des cellules a toujours été un paramètre important dans les réseaux de communication mobile et elle a toujours été un problème dans les zones rurales et industrielles en raison de la longue distance entre les stations de base et les emplacements intérieurs et souterrains en raison des atténuations murales. Pour cela, nous nous intéressons à étudier les cellules femto. Nous présentons un modèle de gain économique pour les fournisseur des services sans fil comme pour les propriétaires des cellules femto afin de promouvoir le mode d’accès hybride aux femtos.
Ensuite, considérons que les réseaux sans fil grandissent très rapidement, il devient évident que le contrôle centralisé ne serait plus pratique pour coordonner tous les élé-ments du réseau et en particulier les problèmes liées aux transmissions. Par conséquent, nous proposons de traiter, dans une troisième partie, le problème du contrôle d’accès au médium afin de réduire les collisions dans les canaux. Nous nous basons sur le protocole d’accès aléatoire "slotted Aloha" et nous introduisons une nouvelle modélisation d’un débit combinée avec des stratégies hiérarchiques pour une étude analytique de l’accès au support dans les réseaux de communication mobile.
Les capacités des réseaux de communication mobile ont explosé au cours de ces dernières années et ont permis la création d’une large gamme d’applications. Ces appli-cations sont pratiquement illimitées. Par conséquent, le besoin a largement augmenté pour établir des régimes capables de stocker les données efficacement, de sauver au-tant d’énergie que possible et de transférer les messages avec une garantie de livraison. Ceci peut être pratiquement effectué dans une analyse du réseau social, qui est l’une des applications les plus populaires dans les réseaux de communication mobile et sans fil. Des millions de gens utilisent chaque jour les réseaux sociaux pour se connecter afin de maintenir des liens d’amitié et d’échange d’idées. Comme résultats, il y a une pléthore
des données d’utilisateur riches et intéressantes diffusées dans les réseaux. Ainsi, nous constatons que les réseaux sociaux contribuent avec une fraction significative au trafic Internet. Cette situation a suscité un intérêt considérable des recherches récentes. Nous terminons notre analyse dans cette thèse par une étude du réseau social où nous nous intéressons à l’interaction entre utilisateurs pour maximiser la vitesse de la diffusion des contenus avec une contrainte de temps et nous assurer l’arrivée de l’information à destination. Ce travail peut être classé dans la couche application. Cette couche utilise les autres couches citées précédemment pour permettre les interactions entre utilisateurs afin que l’information atteigne sa destination dans un délai minimum.
Les grandes lignes de nos principales contributions sont les suivantes:
La Gestion de la Mobilité et la Répartition des Ressources en Temps Réel dans le Réseau Mobile IEEE 802.16e: Dans ce travail, notre objectif est de développer un régime de contrôle d’admission des appels (Call Admission Control : CAC) en temps réel dans le réseau sans fil WiMAX IEEE 802.16e. En utilisant l’adaptation dynamique du lien radio, une cellule IEEE 802.16e est partitionnée en plusieurs régions concen-triques. Chaque région est caractérisée par une modulation (burst profile) affectée par la station de base aux utilisateurs qui se trouvent dans cette région.
En effet, nous proposons deux CACs supportant plusieurs scénarios de partage de ressources selon la mobilité intracellulaire des utilisateurs. En particulier, nous consid-érons deux types de mobilité intracellulaire: La faible mobilité, pour les mobiles qui se déplacent généralement à faible vitesse (correspond aux utilisateurs nomades qui se déplacer en grande partie que vers les régions voisines). La forte mobilité, pour les util-isateurs qui se déplacent à haute vitesse et qui peuvent sauter plus qu’une région avant que la station de base ne change leur modulation. Nous supposons un temps seuil, Tth, qui détermine le temps minimum qu’un appel peut rester dans une région avant que la station de base ne décide de changer sa modulation. Ainsi, Pour chaque mobile, nous comparons le temps estimé qu’il va rester dans une région avec ce seuil Tthpour décider si la station de base va lui changer sa modulation ou non.
En adoptant ce modèle de mobilité, nous introduisons deux régimes CACs. Dans le pre-mière, nous réservons une partie des ressources pour les mobiles en migration, quelque soit leur type de mobilité, forte ou faible. Dans le deuxième CAC, nous donnons la pri-orité seulement pour les utilisateurs en migration avec une forte mobilité. Afin de gérer ces CACs, nous proposons une modélisation basée sur les chaînes de Markov à temps continu. La dimension de la chaîne de Markov est de 2r où r représente le nombre des
régions. L’état du système correspond au nombre des utilisateurs dans chaque région selon leur type de mobilité. Par la suite, nous calculons l’impact de ce modèle proposé sur les probabilités de blocage et de perte. Nous montrons par des résultats numériques qu’avec ces CACs proposés, nous arrivons à trouver une bonne gestion des ressources qui est bien performante sous les différents types de mobilité.
Dans une deuxième partie de ce travail, nous introduisons le problème d’optimisation, afin de trouver un bon compromis entre le choix de perdre les appels en cours de mi-gration ou de bloquer les nouveaux appels entrant dans le système. Pour cela, nous proposons un modèle qui a pour objectif l’optimisation des résultats trouvés dans la pre-mière partie. Notre but est de minimiser à la fois les probabilités de perte et de blocage. Par conséquent, nous définissons une fonction objective à optimiser, afin d’une part d’assurer la meilleure qualité de service pour les utilisateurs et d’autre part de donner le meilleur état de stabilité entre les probabilités de perte et de blocage. Nous montrons par des résultats numérique que la fonction objective proposée donne une allocation des ressources optimale qui permet de garantir une bonne qualité de service pour les nou-veaux appels arrivant dans la cellule et aussi pour ceux en migration.
Mots clés : WiMAX; Forte Mobilité; Faible Mobilité; Allocation des Ressources; Ges-tion de la Mobilité; CAC; OptimisaGes-tion des Résultats.
L’apprentissage d’un Mécanisme de Gain afin de Promouvoir le Mode d’Accès Hybride pour les Femtocellules: Pour les utilisateurs de l’intérieur, le réseau macro seul ne peut pas toujours soutenir la demande croissante des applications gourmandes en bande passante. Sans aucune aide, le réseau macro rencontre des sérieuses difficultés pour le maintien d’une bonne qualité de service. Par conséquent, les femtocellules of-frent une solution intéressante pour répondre aux besoins de capacité du réseau où les mécanismes de contrôle d’accès aux femtocellules jouent un rôle crucial.
Dans ce travail, nous proposons un système d’apprentissage d’un mécanisme de gain pour permettre à un fournisseur de services sans fil d’encourager les propriétaires des femtos situés dans sa zone de couverture à partager leur ressources avec les utilisateurs macro. Nous supposons que les femtocellules adoptent le mode d’accès hybride. Par conséquent, chaque femtocellule va réserver une fraction de ces ressources aux utilisa-teurs macro situés dans sa zone de couverture et en retour il va obtenir un rembourse-ment du fournisseur de services. Pour assurer une qualité de service minimum à tous les mobiles, on suppose que chaque femtocellule ne peut servir qu’un nombre maximum
et prédéfinie des utilisateurs macro et femto à la fois. Notre objectif est d’améliorer la performance globale et de promouvoir le mode d’accès hybride. Pour le réaliser, nous modélisons le système comme un jeu qui se déroule en deux étapes consécutives. Dans un premier temps, le fournisseur de services choisit sa meilleure stratégie illustrée dans le montant total qui est la somme des remboursements qu’il offre aux propriétaires femtos. Et dans un deuxième temps, chaque propriétaire d’un femto i, (i = 1, ..., Z), cherche la meilleure proportion de ressources à allouer aux utilisateurs macro qui sont situés dans sa zone de couverture. L’objectif de chaque joueur est de maximiser sa fonction d’utilité. Nous prouvons l’existence d’un équilibre de Nash de ce jeu. Ensuite, nous proposons deux algorithmes d’apprentissage pour les propriétaires des femtos et le fournisseur de services dans le but d’apprendre à choisir la stratégie optimale sur un ensemble des stratégies admissibles et définies. La stratégie optimale est définie comme l’action qui maximise la probabilité d’être récompensés, ce qui permet d’atteindre une situation gagnant-gagnant.
L’approche d’apprentissage proposée est basée sur des algorithmes d’apprentissage par renforcement. Nous avons choisi les algorithmes suivants: "Linear Reward Inaction " pour les femtocellules et le " Pursuit learning" pour le fournisseur de services. Les ré-sultats numériques montrent que les propriétaires des femtos et le fournisseur de service ont pu bénéficier du mécanisme d’apprentissage de gain proposé pour améliorer leur fonction d’utilité.
Mots clés : Utilisateurs Macro; Utilisateurs Femto; Mode d’Accès Hybride; Mécan-isme de Gain; Algorithmes d’Apprentissage.
Des Stratégies Hiérarchiques pour l’Accès au Médium dans les Réseaux sans Fil: Récemment, le comportement égoïste des utilisateurs mobiles dans les protocoles MAC a été largement analysé en utilisant la théorie des jeux avec tous ses puissants concepts de solution. Ce comportement égoïste provoque la perte et la collision des plusieurs paquets. Pour réduire ce phénomène et pour améliorer la performance du réseau, nous proposons de combiner les algorithmes d’apprentissage, avec une coopération partielle dans le mécanisme Slotted Aloha.
Nous considérons que les mobiles n’ont pas de buffer et que chaque utilisateur ne peut avoir à la fois qu’un seul paquet. Les paquets sont classés en deux types: Premièrement, on a les nouveaux paquets entrants dans le système et qui sont en vue d’être transmis. Deuxièmement, on trouve les paquets backlogged, c.-à-d. les paquets qui sont entrés
en collision avec d’autres transmissions simultanées et qui attendent d’être retransmis. Au début de chaque intervalle de temps (slot), chaque mobile décide soit de transmettre ou non son paquet. La station de base, observe le comportement des mobiles et s’il remarque qu’ils adoptent un comportement qui est très égoïste, son intervention sera d’introduire des transmissions qui ont pour but de bruiter le canal. Ainsi, les mobiles vont détecter une mauvaise qualité du canal et ils vont réduire leurs taux de transmis-sion. Après, nous introduisons la notion de la hiérarchie. Nous développons un jeu de Stackelberg où la station de base est le maitre (leader) et tous les mobiles sont des es-claves (followers). Au début de chaque intervalle de temps, le maître choisit d’abord sa stratégie (transmettre ou non) et la diffuse à ces subordonnées (mobiles) qui choisissent aussi les meilleures stratégies (transmettre ou non) qui vont leur permettre de maximiser leur propre fonction d’utilité. En réalité le jeu est récursif dans le sens où le leader joue un équilibre de Nash sachant (prédisant) le profile des stratégies qui sera décidé par le groupe des followers. Le profile des stratégies décidé par les followers est en fait un équilibre de Nash connaissant la décision des leaders. En fin de compte, il est clair que ce sont les leaders qui décident réellement du sort du jeu. Le point d’équilibre est appelé un équilibre de Stackelberg.
Par la suite, nous définissons une fonction objective pour la station de base. À travers cette fonction, nous donnons à la station de base le choix d’être soit égoïste en imisant son propre débit, ou d’être altruiste en laissant la liberté aux mobiles de max-imiser leur débit séparément. Après, nous introduisons un processus d’apprentissage et nous étudions son impact sur les performances du système. Les résultats obtenus ont montré que cette approche a considérablement amélioré le mécanisme d?une coopéra-tion partiel dans le protocole slotted Aloha, réduit les collisions et garantit un débit stable et non nul.
Mots clés : L’accès au Médium; Stratégies Hiérarchiques; Jeu de Stackelberg; Al-gorithmes d’Apprentissage.
Optimisation du Temps de la Diffusion des contenus via les réseaux sociaux: Jeu d’Apprentissage Stochastique: Plusieurs réseaux sociaux de partage d’informations sont apparus récemment et deviennent concurrents aux réseaux mobiles existants. Parmi les réseaux sociaux les plus populaires on trouve: Facebook, Orkut, LinkedIn, Twiter, YouTube, MySpace et Google Video. Les chercheurs dans la littérature sont intéressés par les problèmes typiques de ces réseaux comme: les architectures complexe qui
dépend des utilisateurs (graph complexe), l’évolution dynamique du réseau, la fonction-nalité du réseau, le partage des contenus en exploitant des liens entre les utilisateurs, la gestion du niveau de la confiance.
En conséquence, Les clients et les entreprises bénéficient beaucoup des ces réseaux où ils cherchent toujours à optimiser le temps de diffusion de leurs messages. Ils essaient de diffuser leurs informations dans le minimum de temps afin de bénéficier le plus de la récompense reçue.
Dans ce travail, nous supposons que chaque noeud du réseau social s’intéresse à diffuser son contenu avec le but d’optimiser son temps de livraison et de vendre ses informations aux récepteurs. Nous considérons la concurrence entre deux sources (vendeurs des con-tenus) qui créent les contenus et qui souhaitent les diffuser dans un temps limité aux récepteurs (les acheteurs des contenus). Nous supposons que chaque source possède ses propres voisins et il est nécessaire pour chaque source de trouver les plus appro-priés d’entre eux qui vont jouer le rôle des relais et permettent de diffuser l’information d’un noeud à un autre jusqu’au l’arrivée à la destination avant l’expiration d’un temps limite. L’objectif de notre travail est de diffuser le contenu à travers des voisins qui se distinguent par un haut degré de connectivité et une haute qualité relationnelle, en termes d’être intéressé à partager le même type d’information. Nous supposons qu’une source peut accélérer la diffusion de son contenu en augmentant la probabilité de partage de l’information entre ses voisins. Aussi, nous supposons qu’une fois l’utilisateur in-téressé reçoit l’information, il sera satisfait et ne nécessitera pas un autre contenu. Dans ce travail, nous essayons de combiner la connectivité et la haute qualité de partage pour diffuser le contenu à son récepteur dans le minimum de temps et dans un environnement concurrentiel. Nous modélisons notre problème comme un jeu d’apprentissage stochas-tique, où chaque joueur tente de maximiser sa fonction d’utilité en sélectionnant l’action optimale en fonction de l’état du système et en fonction de la stratégie adoptée par le concurrent.
Nos principales contributions dans cette partie sont les suivantes:
• Cibler les voisins de la source qui ont une haute connectivité et qui ont plus d’expérience et une meilleure réputation de diffusion des bons contenus.
• Cibler les voisins avec une bonne qualité relationnelle en terme de partager le même type de contenu que la source. Ceci augmentera la probabilité d’arrivée de l’information à sa destination.
valid-ité du contenu. Si ce temps est expiré, ce n’est plus nécessaire de continuer la diffusion.
Les résultats trouvés favorisent notre modèle proposé et nous permettent d’atteindre notre objectif qui est la diffusion des contenus, en ciblant les meilleurs voisins, dans un minimum de temps. Ce modèle proposé peut être intégré dans n’importe quel réseau social et peut être très utile pour les générateurs des contenus, en particulier pour les entreprises qui veulent faire de la publicité à leurs produits et les rendre disponibles aux clients.
Mots clés : Réseaux Sociaux; Temps de Diffusion; Jeu d’Apprentissage Stochastique; Q-Learning; Haute Degré de Connectivité; Haute Qualité Relationnelle.
Contents
Acknowledgments 3 Abstract 5 Résumé 6 Résumé Détaillé 7 List of Acronyms 23Introduction
27
General Context . . . 27Motivation and general overview . . . 32
WiMAX Technology . . . 33
Femtocells Technology . . . 36
Medium Access Control Protocol. . . 37
Social Networks. . . 39
Overview of theoretical concepts considered in this thesis . . . 40
Game theory. . . 40
Reinforcement Learning . . . 42
Learning in games. . . 44
Our contributions . . . 45
Thesis Organisation . . . 48
1 Mobility Management Schemes for Real-Time Traffic and Resource Allo-cation in IEEE 802.16e Mobile Network 49 1.1 Introduction . . . 49
1.1.1 Related work and our Contribution. . . 50
1.1.2 Organization of the chapter. . . 54
1.2 Problem Formulation and Model . . . 54
1.2.1 System description . . . 54
1.2.2 User Mobility Classes Modeling . . . 55
1.2.3 System state and Bandwidth occupancy . . . 57
1.3 System analysis For the first CAC Mechanism . . . 58
1.3.1 Equilibrium distribution . . . 58
1.3.2 Calculation of arrival rate of migrating calls . . . 60
1.3.3 Dropping probabilities . . . 62
1.3.4 Blocking probabilities . . . 63
1.4 System analysis for the second CAC mechanism. . . 63
1.4.1 Dropping probabilities . . . 64
1.4.2 Blocking probabilities . . . 65
1.5 Numerical Investigations . . . 66
1.5.1 Impact of the first CAC mechanism : Case Lm=0 . . . 66
1.5.2 Impact of the first CAC mechanism : Case Lm6=0 . . . 68
1.5.3 Impact of the second CAC mechanism. . . 70
1.6 Optimal bands for resource allocation . . . 75
1.7 Conclusion . . . 81
2 Learning Gain Mechanism to Promote the Femtocells Hybrid Access Mode 83 2.1 Introduction . . . 83
2.1.1 Related Work and our Contribution . . . 85
2.1.2 Organization of the chapter. . . 87
2.2 System model . . . 87
2.3 WSP rewarding mechanism and utilities functions . . . 88
2.3.1 WSP rewarding mechanism . . . 88
2.3.2 Utilities functions. . . 89
2.4 Game model . . . 91
2.4.1 Definition of the game . . . 91
2.4.2 Existence of Nash Equilibrium . . . 92
2.5 Learning Mechanism . . . 93
2.5.1 Pursuit learning algorithm for the WSP . . . 94
2.5.2 Learning algorithm (LR-i) for the femtocells . . . 96
2.6.1 Simulation Setup . . . 97
2.6.2 Results and Observation . . . 98
2.7 Conclusion . . . 100
3 A Combined Throughput and Hierarchical Strategies for Medium Access in Wireless Network 102 3.1 Introduction . . . 102
3.1.1 Related Work and our Contribution . . . 103
3.1.2 Organization of the chapter . . . 105
3.2 Model and problem description . . . 106
3.3 Virtual controller and protocol design . . . 108
3.3.1 Individual performance metrics . . . 114
3.4 Altruism vs selfishness . . . 114
3.5 Learning Mechanism . . . 115
3.5.1 Leader: Policy gradient algorithm . . . 116
3.5.2 Followers: Linear Reward-Inaction(LR-i) Algorithm . . . 117
3.6 Simulation and numerical investigations . . . 117
3.6.1 Stackelberg Equilibruim . . . 118
3.6.2 Learning algorithms . . . 119
3.7 Conclusion . . . 124
4 Optimizing Diffusion Time of the Content Through the Social Networks: Stochastic Learning Game 126 4.1 Introduction . . . 126
4.1.1 Related Work and our Contribution . . . 128
4.1.2 Organization of the chapter . . . 130
4.2 Formulation Model . . . 130
4.2.1 Diffusion policy . . . 133
4.2.2 Formulation of two sources zero-sum stochastic game . . . 133
4.3 Optimal policy of our stochastic game . . . 136
4.3.1 Minimax Q-learning Algorithm . . . 139
4.4 Numerical results . . . 143
4.5 Conclusion . . . 147
Conclusion and Perspectives 149 Summary of Contributions . . . 149
Perspectives: Challenges and Issues . . . 155
List of Figures
1 Mobile Cellular Network Evolution Timeline. . . 28
2 TCP/IP model. . . 30
3 A learning automata tahat interacts with a stochastic unknown envirnment. 44
1.1 OFDMA Cell decomposed into concentric regions. . . 55
1.2 Total blocking probability for all the cell versus λRT0,hand for Lm=0. . . 67
1.3 Dropping probabilities for low and high mobility versus λRT0,h and for
λi,l0 =0.03, Lm=0. . . 67
1.4 Total dropping probability for all the cell versus λRT0,h, λi,l0 and for Lm=0. 68
1.5 Total blocking probability for all the cell versus Lm.. . . 69
1.6 Dropping probabilities versus Lmand for λi,h0 =0.06. . . 69
1.7 Total dropping probability for all the cell versus Lm. . . 70
1.8 Blocking probabilities for high mobility versus Lhighand for λi,h0 =0.06. 71
1.9 Dropping probabilities for high mobility versus Lhighand for λi,h0 =0.06. 72
1.10 Dropping probabilities for low mobility versus Lhighand for λi,l0 =0.06. 72
1.11 Total dropping probability for all the cell versus Lhigh. . . 73
1.12 Dropping probability for the both versus Lmand Lhighfor high mobility. 73
1.13 Dropping probability for the both versus Lmand Lhighfor low mobility.. 74
1.14 The optimized function Pm, with α=0.5, and PBmmaxet PDmmax= 0.2 . . 77
1.15 The optimized function Ph, for high mobility users, versus the reserved
portion of mobility Lhigh. . . 77
1.16 The optimized function Pm, with α =0.2, versus the reserved portion
of mobility Lhigh, and PBmmax =PDmmax =0.2 . . . 78
1.17 The optimized function Pl, versus α, where PBmmax=PDmmax=0.2.. . . 80
1.18 The optimized function Ph, versus α, where PBmmax=PDmmax=0.2. . . 80
2.2 The utility of the WSP Uw and the total amount γ offered by the WSP
to all FHs. . . 98
2.3 The Utility of a FH Uf and the fraction of resource βi. . . 100
3.1 Hierarchical slotted aloha protocol design. . . 110
3.2 Normalized average throughput versus the arrival rate qaof the followers.118
3.3 Retransmission probability at Stackelberg Equilibrium versus the arrival
rate qaof the followers. . . 119
3.4 The average throughput for the leader and followers versus the number
of iterations at the followers arrival rate qa=0.3, and α=0.5. . . 120
3.5 The leader retransmission probability versus the number of iterations at
the followers arrival rate qa=0.3, and α =0.5. . . 120
3.6 The followers retransmission probability versus the number of iterations
at the followers arrival rate qa=0.3, and α =0.5. . . 121
3.7 The average throughput for the leader and followers versus the number
of iterations at the followers arrival rate qa=0.3, and α=0.2. . . 122
3.8 The average throughput for the leader and followers versus the number
of iterations at the followers arrival rate qa=0.3, and α=0.8. . . 122
3.9 The value of α versus the number of iterations at the followers arrival
rate qa=0.3. . . 123
3.10 The average throughput for the leader and followers versus the number
of iterations at the followers arrival rate qa=0.3 with the found α. . . . 124
4.1 Competition between two sources (S1 and S2) to deliver the content to
the receiver on time. The receivers are colored by orange, the neighbors are colored by cyan and finally the sources are colored by green. The
source S1 compares the connectivity of each one of its neighbors (x4,
x5, x6 and x7) to choose the highest. For the relationships quality it
compares the sharing probability(p4,10,p5,11, p5,12,...) at each edge,
then it chooses the neighbor with the highest probability. . . 131
4.2 The value-function of the source versus content validity time at state s1. 143
4.3 The value-function of the source versus content validity time at state s2. 144
4.4 The value-function of the source versus content validity time at state s3. 145
List of Tables
List of Acronyms
1G - First Generation 2G - Second Generation 3G - Third Generation 4G - Fourth Generation 5G - Fifth GenerationAMC - Adaptive Modulation and Coding BE - Best Effort
BLER - Block Error Rate
BPSK - Binary Phase Shift Keying BS - Base Station
CAC - Call Admission Control
CDMA - Code Division Multiple Access CSMA - Carrier Sense Multiple Access CTMC - Continuous Time Markov Chain DSL - Digital Subscriber Line
EDGE - Enhanced Data rates for GSM Evolution ertPS - Extended RReal Time Polling Service FALA - Finite Action-set Learning Automata FAP - Femto Access Point
FBS - Femto Base Station
FBS - Frequency Division Duplexing FDMA - Frequency Division Multiple Access FH - Femto Holder
FWA - Fixed Wireless Access
GPRS - General Packet Radio Service
HSDPA - High Speed Downlink Packet Access HSUPA - High Speed Uplink Packet Access IP - Internet Protocol
LLC - Logical Link Control
LR-I - Linear Reward Inaction learning algorithm LTE - Long Term Evolution
MAC - Medium Access Control MBS - Macro Base Station MC-CDMA- Multi Carrier-CDMA
MIMO - Multiple Input Multiple Output MU - Macro User
MWA - Mobile Wireless Access NE - Nash Equilibrium
nrtPS - Non Real Time Polling Service
OFDMA - Orthogonal Frequency Division Multiple Access QAM - Quadrature Amplitude Modulation
QoS - Quality Of Services
QPSK - Quadrature Phase Shift Keying RT - Real Time
rtPS - Real Time Polling Service RWP - Random WayPoint
SA - Slotted Aloha SER - Symbol Error Rate
SINR - Signal to Interference plus Noise Ratio SNR - Signal-to-Noise Ratio
SON - Self Organizing Network TCP - Transmission Control Protocol TDD - Time Division Duplexing TDMA - Time Division Multiple Access UDP - User Datagram Protocol
UDP - Unsolicited Grant Scheme
UMTS - Universal Mobile Telecommunications textbfSystem WCDMA - Wideband Code Division Multiple Access
Wi-Fi - Wireless Fidelity
WLAN - Wireless Local Area Network
WMAN - Wireless Metropolitan Area Network
WMCN - Wireless and Mobile Communications Networks WSP - Wireless Services Provider
General Context
The field of wireless and mobile communication has a remarkable history that spans over a century of technology innovations from Marconi’s first transatlantic transmis-sion in 1899 to the worldwide adoption of cellular mobile services by over four billion people. The wireless and mobile communication has grown very fast and has evolved tremendously in the last 4 decades. Until very recently, wired network was needed to get online, but now even wired telephones are becoming a thing of past. Wireless has become one of the most pervasive core technology enablers for a diverse variety of computing and communications applications. This has led to an accelerating pace of research and development in the wireless area, with the advanced techniques emerging in all the fields of mobile and wireless communications.
Mobile communications and wireless networks are developing at an astounding speed, with evidences of significant growth in the areas of mobile subscribers and ter-minals, wireless access networks, and mobile services and applications. A new mobile generation has appeared every 10th years. The cellular wireless generation (G) generally refers to a change in the fundamental nature of the service, non-backwards compatible transmission technology, and new frequency bands. The history of mobile telephony (see figure 1) began in 1980’s when the first-generation (1G) voice-only analog net-works were introduced. They were replaced by the second-generation (2G) that started to roll out in 1992 digital phones equipped with fax, data and messaging services. The third generation (3G) appeared in 2001 and ushered in the era of multimedia computing and entertainment on mobile phones. In 2011 all IP Switched networks (4G) comes. And today we are at the cusp of a wireless revolution with superior fifth-generation (5G), which is already upon us [83,88].
• The First Generation: First-generation mobile systems used analogue transmis-sion for speech services. (NMT, C-Nets, AMPS, TACS) are considered to be the first analogue cellular technology. 1G network were conceived and designed purely for voice calls with almost no consideration of data services. It had limi-tation because there was no encryption, the sound quality was poor and the speed of transfer was only at 9.6kbps. It has FDMA in multiplexing possess circuit. • The Second Generation: The concept of 2G is based on multiple base stations
where each station distributed uniformly over the world to communicate with the users. The second-generation (2G) systems use digital multiple access
technol-Figure 1: Mobile Cellular Network Evolution Timeline.
ogy, such as TDMA (time division multiple access) and CDMA (code division multiple access). Consequently, compared with first-generation, higher spec-trum efficiency, better data services, and more advanced roaming were offered by 2G systems. This 2G technologies make uses of compression decompres-sion algorithm (codec). The family members of this generation are 2G(GSM), 2.5G(GPRS), 2.75G(EDGE) [51].
• The Third Generation: 3G is the advanced generation for mobile communica-tion services based on the technical standards of IMT-2000 including the reliabil-ity and speed (data transfer rates). Beyond mobile telephony, the higher speeds allows the 3G connections in PCs, gaming consoles, tablets and any other portable device that could benefit from a faster and higher internet connection quality. 3G also provides users with better security through user authentication capabilities when communicating with other wireless devices. The two main 3G standards are Wideband Code Division Multiple Access (WCDMA) (UMTS) and Multi Carrier CDMA (MC-CDMA) [51]. Improvements on the 3G standard include 3.5G High Speed Downlink Packet Access (HSDPA) and 3.75G High Speed Uplink Packet Access (HSUPA).
• The Fourth Generation: The main features of 4G communication system is seamless access, personalization, quality of service(QoS) and IP based system. It is characterized by high data rates i.e.20 Mb/s per customer, high mobility,
end-to-end IP transmission and QoS management. The 4G are being devised with the vision of heterogeneity in which a mobile user/device will be able to connect to multiple wireless networks (e.g., WLAN, cellular, WMAN) simultaneously. The multiple access technology used by this generation will be OFDM (Orthogonal Frequency Division Multiplexing), e.g., LTE and WiMAX. There will be seamless integration between all generation networks, which gives rise to interoperable heterogeneous wireless networking.
• The Fifth Generation: The 5G (Fifth Generation Mobile and Wireless Net-works) can be a complete wireless communication without limitation, which bring us perfect real world wireless - World Wide Wireless Web (WWWW). 5G de-notes the next major phase of mobile telecommunications standards beyond the 4G/IMT-Advanced standards that will enhance the system quality and capacity within the limited bandwidth spectrum whose frequency band and Data Band-width will be 3-300GHz "and 1Gbps and higher (as demand)" successively. The innovation of fifth generation is based on the three objectives: (i) Implementation of large scale capacity and large connectivity. (ii) Supporting all diverse set of services, applications and users: all with extremely diverging requirements. (iii) Flexible and efficient use of all available non-contiguous spectrum for: wildly different network deployment scenarios [51].
Wireless and mobile communications networks (WMCN) have been evolved through multiple technologies over a period of several decades, to a stage that they become very complicated in the context of resource control and management. The heterogeneous WMCN now includes a variety of network technologies and topologies (e.g. WiMAX, Wi-Fi, LTE.) incorporating with one another to provide a wide range of services; operate in a variety of channel conditions and environments; and within a single universal end user device. WMCN will need to offer global coverage and seamless mobility, enable the use of a universal handheld terminal, and the enhancement of the service quality compared to current wired networks.
Heterogeneous networks must indeed be regarded as a new challenge/solution to offer to the users an efficient and ubiquitous radio access. Several issues related to the development of heterogeneous wireless access networks need to be studied. The research areas the most investigated are the traffic and congestion control; the resource allocation and admission control, the global mobility with QoS support through load balancing and tight integration with services and applications in the higher layers and
the fast and efficient vertical handoff mechanisms.
This thesis covers different aspects of analysis, design, deployment, and optimiza-tion of protocols and architectures for heterogeneous wireless access networks. In par-ticular, the topics include challenges and issues in distributed algorithms design and provisioning of a QoS framework for heterogeneous wireless access networks. Also, it enables a modeling and performance analysis of heterogeneous mobile networks.
As we agree on the assumption that IP will be the core part of the next generation mobile networks (from the 4G), we rely on a TCP/IP architecture layers. A modular ar-chitecture designed based on TCP/IP model (figure2), with modification of the overall protocol stack, removing the modularity character from it, allows interaction of proto-cols with layers other than the adjacent one (e.g. The Cross-Layer architecture design) The TCP/IP layers is normally considered to be as follows:
Figure 2: TCP/IP model.
• Physical layer: Multiple physical network interfaces (cellular, WLAN, WiMax,...); • Link layer: Responsible for communications between adjacent network nodes.It
handles the data moving in and out across the physical layer. It also provides a well defined service to the network layer. Data link layer is divided into two sub layers. The Medium Access Control (MAC) and logical Link Control (LLC).
– MAC: Responsible for regulating access to the shared medium. It deter-mines who is allowed to access the medium at any one time and gives the
permission to transmit data.
– LLC: Provides flow control, acknowledgement, and error notification. It specifies which mechanisms are to be used for addressing stations over the transmission medium and for controlling the data exchanged between the originator and recipient machines.
• Network layer: Faster and easier routing techniques with less signaling and IP global (and heterogeneous) address translations;
• Transport layer: More wireless friendly transport protocols (than TCP and UDP); • Application layer: provides services for an application program to ensure that
effective communication with another application program in a network is possi-ble.
the Cross-layer coordination between different entities within the architecture would be necessary in WMCN. It is necessary for wireless system discovery to provide a list of access networks and their associated QoS parameters in order to support QoS enabled application, direct communication between application layer and QoS sub-layer. Also, to provide services in a visited network based on service policy and subscriber pro-files signaling between mobility management sub-layer and services sub-layer as well as between services layer with resource management and QoS management sub-layer. Also for accounting purpose using information related to the resources used, QoS provided, time and duration of provision of network resources, etc.
Most of the available bibliography focuses on a joint physical and link layers adap-tation. It has been explained in [45] that physical and link layers are very important especially in wireless networks and must be taken into account during cross-layer adap-tation and optimization. Moreover, the application layer has been used in several cross-layer adaptation schemes [89]. While the above mentioned layers (Physical, Link and Application) have been extensively researched in cross-layer adaptation schemes. There has been little work done in the whole protocol stack.
Through this dissertation, we attempt to cover different aspects of analysis and op-timization problems and architectures of heterogeneous WMCN. For doing this, we try to browse through the TCP/IP layers. We are interested more particularly in the Physic, Link and Application layers. We begin with the physical layer and its interaction with the link layer, where we try to study the case of both large and small cells. Then, in the link layer, we intend to treat the problem related to the channel access controls. And we
finish with a practical case in the application layer by addressing a problem in the social networks.
Motivation and general overview
Heterogeneous WMCN systems will achieve efficient wireless resource utilization, seam-less handoff, global mobility with quality of service support through load balancing and tight integration with services and applications in the higher layers. Therewith, new technologies beyond 3.5G (e.g WiMAX, LTE)are being utilized in these cellular net-works. Besides new advanced technologies are actually about dimensioning for planing and optimizing 5G networks, while upgrading 4G networks. Existence of all these technologies in one cellular network has brought the work of networks design and opti-mization to be viewed from different perspective.
In this thesis, we propose a multi-layer analysis where we expect to explore the per-formance evaluation of heterogeneous networks. First, we deal the case of large cell, we choose an OFDMA- based IEEE802.16 WiMAX network cell. Then, we propose resource allocation and mobility management schemes in the presence of real time traf-fic.
And as coverage has always been an important issue in WMCN and also it has tradi-tionally been a problem in rural areas due to the long distance between base stations and indoor and underground locations due to the wall attenuations, we propose secondly to study the case of small cells that offer different approach to these problems. Smaller cell sizes such as femtocells, picocells or nanocells have been used to gain more capac-ity and to improve coverage inside buildings, basements and subway tunnels. In this dissertation we focus on femtocells, whither we present an economic gain framework for wireless service provider and femtocell holders to promote the hybrid access mode. Thereafter, and seeing that the wireless networks grew larger, it becomes evident that centralized control would be impractical for coordinating all elements of the network, and in particular end-user transmissions. Therefore, we choose thirdly to deal with the under-utilization problem of medium access control in wireless collision channels. We base on the random access slotted aloha mechanism to introduce a new modelling frame-work with a combined throughput and hierarchical strategies for an analytical study of the medium access in WMCN.
for a wide range of applications to be created. Those applications are practically unlim-ited. Therefore the need arises for schemes to be able to store data efficiently, save as much energy as possible and transfer messages with guaranteed delivery. This can be easily performed by social network analysis that is one of the most popular applications in the WMCN. Millions of people connect with one other and maintain friendship or exchange ideas using the available online social networks. As results, there is a plethora of rich and interesting user data spread across the networks. So, social networks con-tribute in a significant fraction of Internet traffic. This situation has spurred considerable recent research interest. For that, last but not least, in this thesis, we finish our analysis with an integration in the application higher layer where we intend to study the speed up of contents diffusion within a time constraint between users in social networks. The application layer uses the previous cited layers to enable the interactions between users to ensure that the information reaches its destination in a minimum delay .
As we have mentioned above, through this dissertation, we try to treat and anal-yse the performance of several technologies. Hereafter, we give an overview of these technologies and explain our choice and motivations. We present in succession the IEEE802.16 WiMAX technology, femtocells technology, Medium access control pro-tocol and social networks.
WiMAX Technology
WiMAX (Worldwide Interoperability for Microwave Access) is the commonly used name for broadband wireless access based on the IEEE 802.16 family of standards. WiMAX is also known as IEEE Wireless MAN (Metropolitan Area Network). It stands for worldwide interoperability for microwave access technology support that offers ro-bust services to users and equal to a digital subscriber line. It is full duplex service with uplink and downlink channel. The long range of WiMAX provides quality of services (QoS), scalable architecture and high data throughput. WiMAX is a wireless broadband solution that offers a rich set of features with a lot of flexibility in terms of deployment options and potential service offerings. IEEE802.16d, IEEE802.16e and IEEE802.16m are standards for Wireless Metropolitan Area Network. In parallel the WiMAX forum releases several technical specification profiles [70]. Together they make WiMAX one of the most promising technologies for broadband wireless access solution, as well as a 4G candidate.
IEEE 802.16.e is working in 2-6 GHz band which supports mobility broadband wireless access air interface standard. IEEE 802.16e is designed to achieve both high-speed data services and enable mobile users with broadband wireless access solutions. In the IEEE 802.16 standard for wireless metropolitan area network (WMAN) in 2004, the IEEE 802.16d standard was published for fixed wireless access (FWA) application. In December 2005, the IEEE ratified the 802.16e amendment, which aimed to sup-port mobile wireless access (MWA) with seamless network coverage. This standard is now receiving considerable industrial attention. Based on IEEE 802.16 series standard, WiMAX intend to provide the wireless access over the long distances in a diversity of ways from point to point links to full mobile cellular types access. It achieves around 50 km wireless signal transmission, which cannot be achieved by wireless LAN. The network coverage area is 10 times more than 3G towers. Through the construction of a small number of base stations, the city will be able to achieve full coverage. This makes the wireless network expand the range of applications, providing access speed ups to 70 Mb/s [70,57].
The various key features of WiMAX networks that distinguish it from the other metropolitan area wireless access technologies are [70]:
• Its use the OFDMA (Orthogonal Frequency Division Multiple Access); • Scalable use of the spectrum width (i.e varying from 1.25 MHz to 28 MHz); • Time and Frequency Division Duplexing (TDD and FDD);
• Advanced antenna procedures such as the beam forming, Multiple Input Multiple Output (MIMO);
• Per subscriber adaptive modulation;
• Advanced coding procedures such as space-time coding and turbo coding; • Strong security and Multiple QoS classes appropriate not only for voice but
de-signed for the combination of data, voice and the video services.
The IEEE 802.16e standard is expected to support the QoS for real-time applica-tions, including Voice over Internet Protocol and video streaming with different QoS re-quirements [8]. The IEEE 802.16e standard defined five service classes to describe the QoS requirements in different applications that are: Unsolicited Grant Scheme (UGS); Extended Real Time Polling Service (ertPS); Real Time Polling Service (rtPS); Non Real Time Polling Service (nrtPS) and Best Effort Service (BE). Each of these classes
has its own QoS parameters such as minimum throughput requirement and delay jitter constraints [81].
Recently, researchers are focusing on enhancing the various aspects of WiMAX im-plementation as QoS, Scheduling, Fairness, Throughput, security and complexity of algorithms. In this dissertation, we are more interested in the resource allocation. The resource allocation is used to assign the resources to different demanding entities in the system and scheduling the requests of different users in a well organized way. And since the bandwidth in any network is an asset and is limited, so the performance of the system depends on the network efficient resource utilization. Improving the effi-ciency of resources allocation plays a vital role. A good resource allocation scheme will increase the spectrum efficiency and provide the available resources to the user in best and efficient manner [81]. In Orthogonal Frequency Division Multiple Access (OFDMA) system, the resource allocation is a process to allocate sub carrier with ade-quate resources, while remain connected to the network. The bandwidth is divided into sub carriers. These subcarriers are allocated to the different subscriber and controlled by the BS. The policy of resource allocation depends on the BS. Grouping of these carriers is called as sub-channel and these sub-channels are represented by different Frequency Division Multiple Access (OFDM) symbols known as slots [57].
Considering the literature review related to resource allocation in WiMAX, there are different mechanisms. Currently, the process of resource allocation can be enhanced. In this thesis we aim to find a solution to the issue of how users should be assigned to exploit those resources more efficiently. To answer this question, we introduce several call admission control schemes according to a proposed mobility model. Call admission control is a mechanism of controlling new connections that want to connect to the net-work where the base station decides whether to accept or reject new connections based on the available resource and QoS requirements. Call admission control also manages the change of mobile modulation in the same cell when the users move from one re-gion to another. As the mobile will go away from the base station it will need more resource and the base station risk of interrupting the call if it does not have the required resources. By this thesis, we try to propose a new model that permit to the base sta-tion a good management for its resource and allow it to accept more new calls without dropping the existent connections.
Femtocells Technology
Networks that include smart entities and functionalities, and that allow to fulfill all the mobile networks’ new requirements are called heterogeneous networks. Heterogeneous networks integrate new techniques and low-power smart nodes (small cells), (i.e. femto-cell and picofemto-cells), into traditional femto-cells, (i.e. macrofemto-cells, microfemto-cells, metrofemto-cells and re-peaters) [79]. The gains introduced by these networks are basically due to the reduction of the distance between transmitters and receivers, which increases the network capacity per unit area, the ubiquitous coverage and the spectral efficiency. One key component in heterogeneous networks is femtocells. Femtocells are low range, low power mobile base stations deployed by the end consumers, which underlay the macrocell system and provide a solution to the problem of indoor coverage for mobile communications. Fem-tocells drop off the macrocell load and, therefore, macrocells can devote their resources exclusively to outdoor and mobile communications. Furthermore, the energy consump-tion decreases significantly because femtocells have very low transmission powers and are active only when needed. Femtocells can reuse the radio spectrum and, thereby, they allow increasing the spectral efficiency. Moreover, under appropriate algorithms for interference control, they give a viable alternative to the problem of spectrum static allocation.
While femtocells technology clearly offers users a number of benefits, there are sig-nificant technical, regulatory and economic challenges that need to be met. we mention below a few of them.
Since femtocells are deployed arbitrarily, the biggest challenge in their deployment is to manage interference. Two types of interference can occur: between the macrocell and femtocell users, which is known as cross tier interference and amongst the femto-cells which is referred to as co-tier (inter-femto) interference. Mitigation of interference between macrocells and femtocells, and among femtocells is crucial for efficient oper-ation. Depending upon the operating spectrum for the macro and femtocells, the inter-ference scenario may change. For example, if the macrocell and femtocell operate on different dedicated spectrum, then there will be no cross-tier interference. Conversely, if both operate in the same band, there will potentially be both cross and co-tier inter-ference. The trend is then to develop specialized and competent intercell interference coordination techniques that allow multiple cells to coexist while working on the same frequency band.
Also, coexistence and management tasks of various types of nodes in the mobile net-work require self-responsive and intelligent forms of organization, in such a way that entities have the ability to understand and react to the environment in an autonomous manner. Furthermore, in cellular networks, the growing number of different types of nodes implies a notable increase in the number of network parameters with complex interdependencies that have to be considered and optimized. This can be achieved by introducing the concept of self-organization. Then, components of selforganized sys-tems must be able to evolve behaviours without planning actions, changing its structure and function as a result of the sum of all the interactions of its components and the en-vironment as a whole. Currently, self-organizing capabilities contemplated in wireless systems can be classified in self-configuration, self-optimization and self-healing.
As well, there are many others issues that need to be solved in terms of as example the handover, the QoS provided by the backhaul, the timing and synchronization, and the low power consumption. The femtocell technology looks very promising, but several research is needed in this field. In this thesis, we will embark on developing user’s access mode, to promote the hybrid mode that may represent the optimum solution for macro cells to offload the traffic .
Medium Access Control Protocol
The medium access control (MAC) data communication protocol is a sub layer of the data link layer (layer 2). The MAC sub layer provides addressing and channel ac-cess control mechanisms that make connection possible for several terminals or net-work nodes to communicate within a multiple access netnet-work that incorporates a shared medium. The MAC sub layer acts as an interface between the logical link control (LLC) sub layer and the physical layer. The main job of the MAC protocol is to tell to each node when it can transmit and when it is expected to receive data. The multiple access protocol, is the core of the MAC protocol.
The multiple access protocol may detect or avoid data packet collisions if a packet mode contention based channel access method is used, or resources reservation is es-tablished for a logical channel if a circuit-switched or channelization-based channel access method is used. The multiple access protocol must ensure fairness and efficiency in bandwidth sharing.
sys-tem typically has more users than can be accommodated simultaneously. This is where random access strategies come into picture, making sure that the channel and other re-sources in the network are effectively shared between the active users. For that, we try to identify hereafter the fundamental and most widespread distributed multiple random access protocols that are used almost universally in a vast majority of WMCN.
• Pure Aloha: Whenever a terminal has data, it transmits. Sender finds out whether transmission was successful or experienced a collision by listening to the broad-cast from the destination station. Sender retransmits after some random time if there is a collision.
• Slotted Aloha: Improvement of pure aloha protocol. Time is slotted and a packet can only be transmitted at the beginning of one slot. Thus, can reduce the collision duration.
• CSMA:(Carrier Sense Multiple Access) Start transmission only if no transmis-sion is ongoing.
– 1-persistent CSMA: Sense channel, if channel is busy, then sense continu-ously, until the channel is idle, at this time, transmit the frame immediately. – Non-persistent CSMA: Sense channel, if channel is busy, run backoff al-gorithm immediately to wait a random time and then re-sense the channel again.
– p-persistent CSMA: Sense channel, if channel is busy, then persist sensing the channel until the channel becomes idle. If the channel is idle, transmit the packet with probability p, or wait next slot with probability 1-p, additional propagation delay and then re-sense again and transmit with probability p . • CSMA/CD: (CSMA with Collision Detection) Stop ongoing transmission if a
collision is detected.
• CSMA/CA: (CSMA with Collision Avoidance) Wait a random time and try again when carrier is quiet. If still quiet, then transmit.
The problem of scarcity of resources in WMCN is often addressed through Medium Access Control (MAC) layer design. The medium access control protocols enable com-municating stations at diverse locations to regulate the movement of their packets and manage network bandwidth in order to utilize the network resources as efficiently as possible. The quality-of-service (QoS) of networks is critically dependent on the MAC
protocol used for communication between the nodes. A wide range of MAC protocols have been proposed or developed for different operating environments with different user requirements. The challenge becomes to decide what system performance metric to optimize, which MAC protocol to apply in order to get the best performance, and which system parameter values to choose in order to reach a desired goal of perfor-mance.
In this dissertation, the performance of the most widely used MAC protocols, namely SLLOTED ALOHA, are investigated in terms of the throughput performance metric. Modern wireless networks protocol are often based on Aloha-related concepts (802.11, 802.16 standards) [1]. Despite the extensive interest and research done, the design of such protocol raises novel challenges and many problems still remain unsolved. There-fore, in this thesis, we try to analyse the performance of slotted aloha protocol and propose a combined throughput and hierarchical strategies for medium access in wire-less and mobile communication network in order to increase the whole system perfor-mances.
Social Networks
Online social networks represent a new kind of network design that differs significantly from existing networks like the Web. For example, in the Web, hyperlinks between content form a graph that is used to organize, navigate, and rank information. However, in online social network few links exist between content and instead, the links exist be-tween content and users, and bebe-tween users themselves.
Unlike the traditional Web, which is largely organized by content, online social net-works embody users as first-class entities. Users join a network, publish their own content, and create links to other users in the network called friends. This basic user-to-user link structure facilitates online interaction by providing a mechanism for organizing both real-world and virtual contacts, for finding other users with similar interests, and for locating content and knowledge that has been contributed or endorsed by friends.
The extreme popularity and rapid growth of these online social networks represents a unique opportunity to study their properties, where the understanding of the mechanics and dynamics of these networks is a critical research objective. However, little is known in the research community about the properties of online social network graphs at scale, the factors that shape their structure, the ways they can be leveraged in information systems or the controlling of information propagation and, obviously the wide diversity
in users profiles. Which proves to be a challenging task to develop predictive models for information diffusion in online social networks.
Information diffusion is a generic concept that refers to all processes of propagation in a system, regardless of the nature of the object in motion. This process seems very interesting, especially for companies that are attracted to disseminate their advertising messages on social networks due to their popularities and the low cost that they offer compared with the television channels or cellular networks that are much more expen-sive.
For modelling the diffusion of information in social network, we distinguish two types of models, explanatory and predictive. Concerning predictive models, on the one hand there are non-graph based methods, that are limited by the fact that they ignore the topology of the network and only forecast the evolution of the rate at which information globally diffuses. On the other hand, there are graph based approaches that are able to predict who will influence whom. However, they cannot be used when the network is unknown or implicit.
In this thesis, we are interested in accelerating the diffusion of contents in accordance with a time constraint. We assume that the spreading process are explained by the topol-ogy of the network and the interactions that occur through it, between pairs of users, on the basis of proposed properties.
Overview of theoretical concepts considered in this thesis
Through the chapters of this dissertation, we base our analyse the most on methods and tools that are well known, have been widely used in the literature and have repeatedly demonstrated their efficiency and robustness. In this section, we try to introduce some of these basic theoretical concepts.
Game theory
Game theory is a powerful tool that has been widely used in different fields to study the behavior of interacting actors having conflicting interests. It has been applied in real games, economics, politics, commerce and recently in telecommunications and net-working. For instance, intensive research effort has been devoted to game models in
wireless networks.
Game theory is a discipline aimed at modeling scenarios where individual decision-makers have to choose specific actions that have mutual or possibly conflict conse-quences. A game consists of three major components:
• players: The decision makers are called players, denoted by a finite set N =
{1, 2, ..., n}.
• strategy: Each player i ∈ N has a non-empty strategy set S. Let si denotes the
selected strategy by player i. A strategy profile s consists of all players’ strategies, i.e., s= (s1, s2, ..., sn). Obviously, we have s ∈ S=xi∈NSi, where x is the Cartesian
product.
• utility/payoff: The utility of player i is a measurement function, denoted by ui:
S→R, on the possible outcome determined by the strategies of all players, where
R is the set of real numbers.
The players of the game are assumed to be rational and selfish, which means that each player is only interested in maximizing its own utility without respecting others’. In order to study the interactions among players, the concept of Nash Equilibrium (NE) is introduced. A strategy profile constitutes an NE if none of the players can improve its utility by unilaterally deviating from its current strategy.
Existence and uniqueness of NE: The existence of NEs in a game is always one of the properties investigated by the researchers. The reason is that an NE is a solution concept that describes a steady state condition of the game. If the existence of NE is not guaranteed, it is possible that players oscillate their strategies to improve their utilities, generating a significant amount of communication overhead and wasting computing resources. Besides the existence, the uniqueness of NE is another desirable property, which has been largely neglected by the existing works. If there is only one NE, players will not be confused while selecting their NE strategies. In addition, we can predict the NE of the game and the resulting performance.
Still in relation with the game theory, we can classify games into three fundamental categories:
• games in strategic form ( or games in normal form); • games in extensive form( or tree games);
