Modélisation et distribution adaptatives de grandes scènes naturelles

Cette thèse traite de la modélisation et la diffusion de grandes scènes 3D naturelles. Nous visons à fournir des techniques pour permettre à des utilisateurs de naviguer à distance dans une scène 3D naturelle, tout en assurant la cohérence botanique et l'interactivité. Tout d'abord, nous fournissons une technique de compression multi-résolution, fondée sur la normalisation, l'instanciation, la décorrélation, et sur le codage entropique des informations géometriques pour des modèles de plantes. Ensuite, nous étudions la transmission efficace de ces objets 3D. L'algorithme de paquétisation proposé fonctionne pour la plupart des représentations multi-résolution d'objet 3D. Nous validons les techniques de paquétisation par des expériences sur un WAN (Wide Area Network), avec et sans contrôle de congestion (Datagram Congestion Control Protocol). Enfin, nous abordons les questions du streaming au niveau de la scène. Nous optimisons le traitement des requêtes du côté serveur en fournissant une structure de données adaptée et nous préparons le terrain pour nos travaux futurs sur l'évolutivité et le déploiement de systèmes distribués de streaming 3D. ABSTRACT : This thesis deals with the modeling and the interactive streaming of large natural 3D scenes. We aim at providing techniques to allow the remote walkthrough of users in a natural 3D scene ensuring botanical coherency and interactivity.First, we provide a compact and progressive representation for botanically realistic plant models. The topological structure and the geometry of the plants are represented by generalized cylinders. We provide a multi-resolution compression scheme, based on standardization and instantiation, on difference-based decorrelation, and on entropy coding. Then, we study efficient transmission of these 3D objects. The proposed packetization scheme works for any multi-resolution 3D representation. We validate our packetization schemes with extensive experiments over a WAN (Wide Area Network), with and without congestion control (Datagram Congestion Control Protocol). Finally, we address issues on streaming at the scene-level. We optimize the viewpoint culling requests on server-side by providing an adapted datastructure and we prepare the ground for our further work on scalability and deployment of distributed 3D streaming systems

Network Traffic Measurements, Applications to Internet Services and Security

The Internet has become along the years a pervasive network interconnecting billions of users and is now playing the role of collector for a multitude of tasks, ranging from professional activities to personal interactions. From a technical standpoint, novel architectures, e.g., cloud-based services and content delivery networks, innovative devices, e.g., smartphones and connected wearables, and security threats, e.g., DDoS attacks, are posing new challenges in understanding network dynamics. In such complex scenario, network measurements play a central role to guide traffic management, improve network design, and evaluate application requirements. In addition, increasing importance is devoted to the quality of experience provided to final users, which requires thorough investigations on both the transport network and the design of Internet services. In this thesis, we stress the importance of users’ centrality by focusing on the traffic they exchange with the network. To do so, we design methodologies complementing passive and active measurements, as well as post-processing techniques belonging to the machine learning and statistics domains. Traffic exchanged by Internet users can be classified in three macro-groups: (i) Outbound, produced by users’ devices and pushed to the network; (ii) unsolicited, part of malicious attacks threatening users’ security; and (iii) inbound, directed to users’ devices and retrieved from remote servers. For each of the above categories, we address specific research topics consisting in the benchmarking of personal cloud storage services, the automatic identification of Internet threats, and the assessment of quality of experience in the Web domain, respectively. Results comprise several contributions in the scope of each research topic. In short, they shed light on (i) the interplay among design choices of cloud storage services, which severely impact the performance provided to end users; (ii) the feasibility of designing a general purpose classifier to detect malicious attacks, without chasing threat specificities; and (iii) the relevance of appropriate means to evaluate the perceived quality of Web pages delivery, strengthening the need of users’ feedbacks for a factual assessment