Integrating context-awareness in the ip multimedia subsystem for enhanced session control and service provisioning capabilities
Notice bibliographique
Résumé
The 3GPP-defined IP Multimedia Subsystem (IMS) is becoming the de-facto standard for IP-based multimedia communication services. It consists of an overlay control and service layer that is deployed on top of IP-based mobile and fixed networks. This layer encompasses a set of common functions (e.g. session control functions allowing the initiation/modification/termination of sessions) and service logics that are needed for the seamless provisioning of IP multimedia services to users, via different access technologies. As it continues to evolve, the IMS still faces several challenges including: the enabling of innovative and personalized services that would appeal to users and increase network operators' revenues; its interaction with other types of networks (e.g. wireless sensor networks) as means to enhance its capabilities; and the support of advanced QoS schemes that would manage the network resources in an efficient and adaptive manner. The context-awareness concept, which comes from the pervasive computing field, signifies the ability to use situational information (or context) in support to operations and decision making and for the provision of relevant services to the user. Context-awareness is considered to enhance users' experience and is seen as an enabler to adaptability and service personalization - two capabilities that could play important roles in telecommunication environments. This thesis focuses on the introduction of the context-awareness technology in the IMS, as means to enhance its session control and service provisioning capabilities. It starts by presenting the necessary background information, followed by a derivation of requirements and a review of the related work. To ensure the availability of contextual information within the network, we then propose an architecture for context information acquisition and management in the IMS. This architecture leverages and extends the 3GPP presence framework. Building on the capabilities of this architecture, we demonstrate how the managed information could be integrated in IMS operations, at the control and service levels. Showcasing control level integration, we propose a novel context-aware call differentiation framework as means to offer enhanced QoS support (for sessions/calls) in IMS-based networks. This framework enables the differentiation between different categories of calls at the IMS session control level, via dynamic and adaptive resource allocation, in addition to supporting a specialized charging model. Furthermore, we also propose a framework for enhanced IMS emergency communication services. This framework addresses the limitations of existing IP-based emergency solutions, by offering three main improvements: a QoS-enhanced emergency service; a context-aware personalized emergency service; and a conferencing-enhanced emergency service. We demonstrate the use of context awareness at the IMS service level using two new context-aware IMS applications. Finally, to validate our solutions and evaluate their performance, we build various proof-of-concept prototypes and OPNET simulation models.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».