With the proliferation of mobile applications and the abundance of wireless devices, it is increasingly common for devices to support multiple radios. When two devices are communicating they should choose the best available radio based on user preference and application requirements. This type of “radio switching” should happen automatically, so that the system optimizes performance dynamically. To achieve this objective, we design an Autonomous and Intelligent Radio Switching (AIRS) system to leverage the radio heterogeneity common in today's wireless devices. The AIRS system consists of three key components. First, we design a radio preference evaluation module to dynamically select the best radio according to users' preference, application's QoS requirements, and the device battery usage. Second, we propose a link quality measurement and prediction module to predict the radio quality under a variety of mobility and interference conditions. Third, we present a radio switching decision making module to switch to the preferred available radio intelligently, based on the preference and link quality evaluations. The AIRS system maintains connectivity, as well as improves link quality, via dynamic and intelligent radio switching, regardless of interference or collisions from the interfaces of other devices. The radio preference evaluation module is able to generate and adjust a preference list dynamically. Multiple users' requirements are satisfied in a mutually beneficial manner and the selected radio is Pareto optimal. The link prediction module is able to achieve an accuracy above 90% under a variety of mobility and interference conditions. The module can dynamically increase the link measurement interval and significantly reduce its power consumption, without sacrificing accuracy. The decision algorithm uses several parameters to avoid switching radios too frequently, and is able to provide dynamic, but stable radio switching, while balancing the competing objectives of high throughput and low power consumption. Overall, the AIRS system is able to achieve high goodput (application level throughput) and long battery life as applied to handoff management in a frequently changing mobile environment.

Constructing common ground and the associated convergent conceptual change is critical to cooperative work and learning. Convergent conceptual change is achieved as participants in a conversation update common ground through presentations, repairs, and acceptances of utterances. People employ available techniques that utilize the least collaborative effort for current purposes. Although sharing physical co-presence of interlocutors' facial expressions doesn't make grounding more efficient even in more open-ended and less task-focused dialogues, visual co-presence of the addressee's workspace is essential to work-related tasks, such as information transmission and collaborative problem-solving. However, handheld-mediated collaborative activity makes sharing the workspace challenging, especially when we consider that handhelds possess small screens and permit activities of a distributed nature. In a handheld-mediated classroom, a teacher must be able to check students' work for various reasons (e.g., grading, checking whether they are following directions correctly or paying attention) and at various phases of the activity. Gazing into the small screen of a handheld over someone's shoulder is a tricky task at best. The teacher may misread the information on the screen and thus provide incorrect feedback. Another challenge involves the difficulty inherent in latecomers joining the collaborative activity when each student is involved with his or her individual and small screen. This exclusion from joining on-going activity can reduce the chance of student's vicarious and serendipitous learning. Although such events may occur naturally in the learning environment, they become important concerns when one attempts to focus collaborative activities with handheld devices. I therefore created a new handheld network service called "Look," which is designed to facilitate the acquisition of common ground and allow a latecomer to do meaningful monitoring of ongoing conversation about the workspace. I tested empirically the value of this shared physical/virtual context in the task of creating common ground by examining task performance and conversation quality. / Ph. D.

Im Rahmen der Dissertation wurde ein Middlewaredienst entwickelt und realisiert. Es gestattet die dynamische Verwaltung heterogener Kontextquellen. Das zugrunde liegende Komponentenmodell selbstbeschreibender Context Provieder ermöglicht die lose Kopplung von Kontextquellen und -senken. Es wird durch Filter- und Konverterkomponenten zur generischen Providersselektion anhand domänenspezifischer Merkmale ergänzt. Die Kopplung der verteilten Dienstinstanzen erfolgt durch ein hybrides Peer-to-Peer-System. Dies trägt der Heterogenität der Endgeräte Rechnung, und erlaubt die skalierbare , verteilte Verwaltung von Kontextquellen in globalen Szenarien.

Weighted granular best matching algorithm is proposed for the operation of context matching in context-aware computing systems. New algorithm deals with the subjective, fuzzy and multidimensional characteristics of contextual information by using weights and a granular structure for contextual information. The proposal is applied on a case: CAPRA &ndash / Context-Aware Personal Reminder Agent tool to show the applicability of the new context matching algorithm. The obtained outputs showed that proposed algorithm produces the results which are more sensitive to the user&rsquo / s intention, more adaptive to the characteristics of the contextual information and applicable to a current Context-aware system.

Avec l'apparition des paradigmes de l'intelligence ambiante et de la robotique ubiquitaire, on assiste à l'émergence de nouveaux systèmes intelligents ambiants visant à créer et gérer des environnements ou écosystèmes intelligents d'une façon intuitive et transparente. Ces environnements sont des espaces intelligents caractérisés notamment par l'ouverture, l'hétérogénéité, l'incertitude et la dynamicité des entités qui les constituent. Ces caractéristiques soulèvent ainsi des défis scientifiques considérables pour la conception et la mise en œuvre d'un système intelligent adéquat. Ces défis sont principalement au nombre de cinq : l'abstraction de la représentation des entités hétérogènes, la gestion des incertitudes, la réactivité aux événements, la sensibilité au contexte et l'auto-adaptation face aux changements imprévisibles qui se produisent dans l'environnement ambiant. L'approche par composition dynamique de services constitue l'une des réponses prometteuses à ces défis. Dans cette thèse, nous proposons un système intelligent capable d'effectuer une composition dynamique de services en tenant compte, d'une part, du contexte d'utilisation et des diverses fonctionnalités offertes par les services disponibles dans un environnement ambiant et d'autre part, des besoins variables exprimés par les utilisateurs. Ce système est construit suivant un modèle multicouche, adaptatif et réactif aux événements. Il repose aussi sur l'emploi d'un modèle de connaissances expressif permettant une ouverture plus large vers les différentes entités de l'environnement ambiant notamment : les dispositifs, les services, les événements, le contexte et les utilisateurs. Ce système intègre également un modèle de découverte et de classification de services afin de localiser et de préparer sémantiquement les services nécessaires à la composition de services. Cette composition est réalisée d'une façon automatique et dynamique en deux phases principales: la phase offline et la phase online. Dans la phase offline, un graphe global reliant tous les services abstraits disponibles est généré automatiquement en se basant sur des règles de décision sur les entrées et les sorties des services. Dans la phase online, des sous-graphes sont extraits automatiquement à partir du graphe global selon les tâches à réaliser qui sont déclenchées par des événements qui surviennent dans l'environnement ambiant. Les sous-graphes ainsi obtenus sont exécutés suivant un modèle de sélection et de monitoring de services pour tenir compte du contexte d'utilisation et garantir une meilleure qualité de service. Les différents modèles proposés ont été mis en œuvre et validés sur la plateforme ubiquitaire d'expérimentation du laboratoire LISSI à partir de plusieurs scénarii d'assistance et de maintien de personnes à domicile / With the appearance of the paradigms of the ambient intelligence and ubiquitaire robotics, we attend the emergence of new ambient intelligent systems to create and manage environments or intelligent ecosystems in a intuitive and transparent way. These environments are intelligent spaces characterized in particular by the opening, the heterogeneousness, the uncertainty and the dynamicité of the entities which establish(constitute) them. These characteristics so lift(raise) considerable scientific challenges for the conception(design) and the implementation of an adequate intelligent system. These challenges are mainly among five: the abstraction of the representation of the heterogeneous entities, the management of the uncertainties, the reactivity in the events, the sensibility in the context and the auto-adaptation