Depuis les années 90, la technologie réseau et radio mobile a fait l'objet de progrès phénoménaux. Cette avancée technologique s'est faite en parallèle du côté réseau, du côté application et du coté besoin de l’utilisateur. L’évolution rapide de la technologie a eu pour conséquence l’existence d’un environnement hétérogène où la couverture est assurée par la coexistence de plusieurs types de réseaux. Le défi soulevé par cette architecture est de pouvoir naviguer entre plusieurs réseaux d’une façon transparente. La navigation entre réseaux de types différents est connue sous le nom du Handover vertical. Le standard IEEE 802.21 offre une composante appelée Media Independent Handover (MIH) qui contient une fonction capable de transmettre l’état des liens du nœud mobile depuis les couches inférieures vers les couches supérieures. MIH s’intercale entre le niveau 2 et le niveau 3 dans la pile protocolaire. Le rôle principal de MIH est d’aider le nœud mobile à faire un transfert sans coupure entre des réseaux de types différents, mais la logique de sélection est laissée sans implémentation.Dans ce contexte nous avons travaillé sur l’amélioration de la gestion du Handover en proposant une nouvelle architecture appelée VHMC et basée sur MIH offrant des nouvelles méthodes de sélection du réseau destination. La première proposition est un nouvel algorithme nommé Multiple Criteria Selection Algorithm (MCSA) basé sur plusieurs paramètres de qualité du service. Nous avons utilisé le simulateur Network Simulator (NS2) pour évaluer nos propositions en étudiant le nombre de paquets perdus et le temps de latence du Handover durant la période du transfert. La deuxième contribution est un nouveau modèle de sélection du réseau destination basé sur la technique de la logique floue. La base d’inférence, qui est l’élément central de la décision de ce modèle, est déduit grâce à une étude basée sur un nombre élevé de cas de Handover réels collectés des serveurs de la compagnie de télécommunication libanaise "Alfa". Une troisième solution est proposée à travers un nouveau modèle de sélection du réseau destination basé sur la théorie de la régression linéaire multiple. / Since 1990, networking and mobile technologies have made a phenomenal unprecedented progress. This progress has been experienced on multiple fronts in parallel; especially on the application level and the user's needs one. This rapid evolution of the technology imposed a need for the existence of heterogeneous environments where the coverage is ensured throughout the different available networks. The challenge with such architecture would be to provide the user with the ability to navigate through the different available networks in a transparent and seamless fashion. However, the navigation among different types of networks is commonly referred to as vertical Handover. The IEEE 802.21 standard offers a component that is called Media Independent Handover (MIH) which has a function that provides the capability of transmitting the state of the connection of the mobile nodes from the lower to upper layers. This layer would exist between layer 2 and layer 3 within the protocol architecture. The main role of MIH is to help the mobile node transfer without interrupt among different types of networks, but the logic of selection is left without implementation. In this context, we worked on the improvement of the Handover management by proposing a new architecture, called VHMC and based on MIH by offering new methods for selecting the destination network. The first solution is a new algorithm called Multiple Criteria Selection Algorithm (MCSA) based on multiple parameters of the quality of service. We used Network Simulator (NS2) for testing our approach and study the number of lost packets and lost time during Handover. The second solution is a new model for selecting the destination network based on fuzzy logic techniques. The distinctive characteristic of this model lies in the study of genuine Handover records taken from a Lebanese mobile operator called "Alfa". A third proposed solution for network selection is based on multiple linear regression theory.

Heterogeneous wireless networking technologies such as satellite, UMTS, WiMax and WLAN are being used to provide network access for both voice and data services. In big cities, the densely populated areas like town centres, shopping centres and train stations may have coverage of multiple wireless networks. Traditional Radio Access Technology (RAT) selection algorithms are mainly based on the 'Always Best Connected' paradigm whereby the mobile nodes are always directed towards the available network which has the strongest and fastest link. Hence a large number of mobile users may be connected to the more common UMTS while the other networks like WiMax and WLAN would be underutilised, thereby creating an unbalanced load across these different wireless networks. This high variation among the load across different co-located networks may cause congestion on overloaded network leading to high call blocking and call dropping probabilities. This can be alleviated by moving mobile users from heavily loaded networks to least loaded networks. This thesis presents a novel framework for load balancing in heterogeneous wireless networks incorporating the IEEE 802.21 Media Independent Handover (MIH). The framework comprises of novel load-aware RAT selection techniques and novel network load balancing mechanism. Three new different load balancing algorithms i.e. baseline, fuzzy and neural-fuzzy algorithms have also been presented in this thesis that are used by the framework for efficient load balancing across the different co-located wireless networks. A simulation model developed in NS2 validates the performance of the proposed load balancing framework. Different attributes like load distribution in all wireless networks, handover latencies, packet drops, throughput at mobile nodes and network utilization have been observed to evaluate the effects of load balancing using different scenarios. The simulation results indicate that with load balancing the performance efficiency improves as the overloaded situation is avoided by load balancing.

Heterogeneous wireless networking technologies such as satellite, UMTS, WiMax and WLAN are being used to provide network access for both voice and data services. In big cities, the densely populated areas like town centres, shopping centres and train stations may have coverage of multiple wireless networks. Traditional Radio Access Technology (RAT) selection algorithms are mainly based on the ¿Always Best Connected¿ paradigm whereby the mobile nodes are always directed towards the available network which has the strongest and fastest link. Hence a large number of mobile users may be connected to the more common UMTS while the other networks like WiMax and WLAN would be underutilised, thereby creating an unbalanced load across these different wireless networks. This high variation among the load across different co-located networks may cause congestion on overloaded network leading to high call blocking and call dropping probabilities. This can be alleviated by moving mobile users from heavily loaded networks to least loaded networks. This thesis presents a novel framework for load balancing in heterogeneous wireless networks incorporating the IEEE 802.21 Media Independent Handover (MIH). The framework comprises of novel load-aware RAT selection techniques and novel network load balancing mechanism. Three new different load balancing algorithms i.e. baseline, fuzzy and neural-fuzzy algorithms have also been presented in this thesis that are used by the framework for efficient load balancing across the different co-located wireless networks. A simulation model developed in NS2 validates the performance of the proposed load balancing framework. Different attributes like load distribution in all wireless networks, handover latencies, packet drops, throughput at mobile nodes and network utilization have been observed to evaluate the effects of load balancing using different scenarios. The simulation results indicate that with load balancing the performance efficiency improves as the overloaded situation is avoided by load balancing.