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Academic literature on the topic 'Tranche de réseau'
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Journal articles on the topic "Tranche de réseau"
Lins de Barros, Myriam Moraes, and Sara Nigri Goldman. "Internet: Y a-t-il une place pour les “vieux”?" Revista Trace, no. 41 (September 5, 2018): 97. http://dx.doi.org/10.22134/trace.41.2002.568.
Full textLambert, Claude. "De la nécessité de Désordre dans la Démocratie." Acta Europeana Systemica 6 (July 12, 2020): 41–48. http://dx.doi.org/10.14428/aes.v6i1.56803.
Full textOlita, Paolo. "L’îlotage : ce qui se joue lorsqu’un réacteur est brutalement coupé du réseau." Revue Générale Nucléaire, no. 1 (2024): 62–63. http://dx.doi.org/10.1051/rgn/20241062.
Full textBaril, Quentin, and Nicolas Samuelian. "Des vestiges méconnus de la Seconde Guerre mondiale : les tranchées-abris du programme de défense passive." Revue d'archéologie contemporaine N° 2, no. 1 (October 23, 2023): 145–58. http://dx.doi.org/10.3917/raco.002.0145.
Full textWawrzyniak, Vincent, Bianca Räpple, Hervé Piégay, Kristell Michel, Hervé Parmentier, and Alice Couturier. "Analyse multi-temporelle des marges fluviales fréquemment inondées à partir d'images satellites Pléiades." Revue Française de Photogrammétrie et de Télédétection, no. 208 (October 23, 2014): 69–75. http://dx.doi.org/10.52638/rfpt.2014.96.
Full textDeschodt, Laurent, Mathieu Lançon, Samuel Desoutter, Guillaume Hulin, François-Xavier Simon, Bruno Vanwalscappel, Yves Créteur, et al. "Exploration archéologique de 170 hectares de plaine maritime (Bourbourg, Saint-Georges-sur-l’Aa, Craywick, Nord de la France) : restitution de la fermeture d’un estuaire au Moyen Âge et mise en évidence de mares endiguées." BSGF - Earth Sciences Bulletin 192 (2021): 12. http://dx.doi.org/10.1051/bsgf/2021004.
Full textPaché, Gilles. "Vendre le Doute: Des Outils de Communication au Service de la Manipulation des Masses." European Scientific Journal, ESJ 19, no. 20 (July 31, 2023): 86. http://dx.doi.org/10.19044/esj.2023.v19n20p86.
Full textDe Matos-Machado, Rémi, Jean-Pierre Toumazet, and Stéphanie Jacquemot. "Cartographie semi-automatisée et classification des réseaux de tranchées et boyaux du champ de bataille de Verdun à partir du LiDAR aéroporté." Archéologies numériques 4, no. 1 (2020). http://dx.doi.org/10.21494/iste.op.2020.0525.
Full textSliwinski, Alicia. "Globalisation." Anthropen, 2018. http://dx.doi.org/10.17184/eac.anthropen.084.
Full textDe la Croix, David, Frédéric Docquier, and Bruno Van der Linden. "Numéro 72 - septembre 2009." Regards économiques, October 12, 2018. http://dx.doi.org/10.14428/regardseco.v1i0.15453.
Full textDissertations / Theses on the topic "Tranche de réseau"
Patry, Jean-Luc. "Intégration sur tranche d'une architecture massivement parallèle tolérant les défauts de fin de fabrication." Phd thesis, Grenoble INPG, 1992. http://tel.archives-ouvertes.fr/tel-00341630.
Full textLuu, Quang Trung. "Dynamic Control and Optimization of Wireless Virtual Networks." Electronic Thesis or Diss., université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG039.
Full textNetwork slicing is a key enabler for 5G networks. With network slicing, Mobile Network Operators (MNO) create various slices for Service Providers (SP) to accommodate customized services. As network slices are operated on a common network infrastructure owned by some Infrastructure Provider (InP), efficiently sharing the resources across various slices is very important. In this thesis, taking the InP perspective, we propose several methods for provisioning resources for network slices. Previous best-effort approaches deploy the various Service Function Chains (SFCs) of a given slice sequentially in the infrastructure network. In this thesis, we provision aggregate resources to accommodate slice demands. Once provisioning is successful, the SFCs of the slice are ensured to get enough resources to be properly operated. This facilitates the satisfaction of the slice quality of service requirements. The proposed provisioning solutions also yield a reduction of the computational resources needed to deploy the SFCs
Hurat, Philippe. "APLYSIE : un circuit neuro-mimétique : réalisation et intégration sur tranche." Phd thesis, Grenoble INPG, 1989. http://tel.archives-ouvertes.fr/tel-00332382.
Full textFerraz, Fernando. "Territorialité, techniques et réseau urbain au Brésil : le transit d'une terre en transe." Paris 1, 2006. http://www.theses.fr/2006PA010585.
Full textDomas, Jérémie. "Valorisation de sables issus de boues de curage des réseaux d'assainissementbTexte imprimé : exemple en remblayage de tranchée." Marne-la-vallée, ENPC, 1999. http://www.theses.fr/1999ENPC9933.
Full textSong, Jinyan. "Capteurs optiques intégrés basés sur des lasers à semiconducteur et des résonateurs en anneaux interrogés en intensité." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00811402.
Full textGigout, Sylvain. "Synchronisation des réseaux neuronaux dans l' épilepsie du lobe temporal chez l' homme et l' épilepsie-absences chez l' animal : rôle des jonctions communicantes." Paris 6, 2005. http://www.theses.fr/2005PA066506.
Full textSalhab, Nazih. "Resource provisioning and dynamic optimization of Network Slices in an SDN/NFV environment." Thesis, Paris Est, 2020. http://www.theses.fr/2020PESC2019.
Full textTo address the enhanced mobile broadband, massive and critical communications for the Internet of things, Fifth Generation (5G) of mobile communications is being deployed, nowadays, relying on multiple enablers, namely: Cloud Radio Access Network (C-RAN), Software-Defined Networking (SDN) and Network Function Virtualization (NFV).C-RAN decomposes the new generation Node-B into: i) Remote Radio Head (RRH), ii) Digital Unit (DU), and iii) Central Unit (CU), also known as Cloud or Collaborative Unit.DUs and CUs are the two blocks that implement the former 4G Baseband Unit (BBU) while leveraging eight options of functional splits of the front-haul for a fine-tuned performance. The RRH implements the radio frequency outdoor circuitry. SDN allows programming network's behavior by decoupling the control plane from the user plane and centralizing the flow management in a dedicated controller node. NFV, on the other hand, uses virtualization technology to run Virtualized Network Functions (VNFs) on commodity servers. SDN and NFV allow the partitioning of the C-RAN, transport and core networks as network slices defined as isolated and virtual end-to-end networks tailored to fulfill diverse requirements requested by a particular application. The main objective of this thesis is to develop resource-provisioning algorithms (Central Processing Unit (CPU), memory, energy, and spectrum) for 5G networks while guaranteeing optimal provisioning of VNFs for a cloud-based infrastructure. To achieve this ultimate goal, we address the optimization of both resources and infrastructure within three network domains: 5G Core Network (5GC), C-RAN and the SDN controllers. We, first formulate the 5GC offloading problem as a constrained-optimization to meet multiple objectives (virtualization cost, processing power and network load) by making optimal decisions with minimum latency. We optimize the usage of the network infrastructure in terms of computing capabilities, power consumption, and bitrate, while meeting the needs per slice (latency, reliability, efficiency, etc.). Knowing that the infrastructure is subject to frequent and massive events such as the arrival/departure of users/devices, continuous network evolution (reconfigurations, and inevitable failures), we propose a dynamic optimization using Branch, Cut and Price, while discussing objectives effects on multiple metrics.Our second contribution consists of optimizing the C-RAN by proposing a dynamic mapping of RRHs to BBUs (DUs and CUs). On first hand, we propose clustering the RRHs in an aim to optimize the downlink throughput. On second hand, we propose the prediction of the Power Headroom (PHR), to optimize the throughput on the uplink.We formulate our RRHs clustering problem as k-dimensional multiple Knapsacks and the prediction of PHR using different Machine Learning (ML) approaches to minimize the interference and maximize the throughput.Finally, we address the orchestration of 5G network slices through the software defined C-RAN controller using ML-based approaches, for all of: classification of performance requirements, forecasting of slicing ratios, admission controlling, scheduling and adaptive resource management.Based on extensive evaluations conducted in our 5G experimental prototype based on OpenAirInterface, and using an integrated performance management stack, we show that our proposals outperform the prominent related strategies in terms of optimization speed, computing cost, and achieved throughput
Arora, Sagar. "Cloud Native Network Slice Orchestration in 5G and Beyond." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS278.
Full textNetwork Function Virtualization (NFV) is the founding pillar of 5G Service Based Architecture. It has the potential to revolutionize the future mobile communication generations. NFV started long back in 2012 with Virtual-Machine (VM) based Virtual Network Functions (VNFs). The use of VMs raised multiple questions because of the compatibility issues between VM hypervisors and their high resource consumption. This made containers to be an alternative network function packaging technology. The lightweight design of containers improves their instantiation time and resource footprints. Apart from network functions, containerization can be a promising enabler for Multi-access Edge Computing (MEC) applications that provides a home to low-latency demanding services. Edge computing is one of the key technology of the last decade, enabling several emerging services beyond 5G (e.g., autonomous driving, robotic networks, Augmented Reality (AR)) requiring high availability and low latency communications. The resource scarcity at the edge of the network requires technologies that efficiently utilize computational, storage, and networking resources. Containers' low-resource footprints make them suitable for designing MEC applications. Containerization is meant to be used in the framework of cloud-native application design fundamentals, loosely coupled microservices-based architecture, on-demand scalability, and high resilience. The flexibility and agility of containers can certainly benefit 5G Network Slicing that highly relies on NFV and MEC. The concept of Network slicing allows the creation of isolated logical networks on top of the same physical network. A network slice can have dedicated network functions or its network functions can be shared among multiple slices. Indeed, network slice orchestration requires interaction with multiple technological domain orchestrators, access, transport, core network, and edge computing. The paradigm shift of using cloud-native application design principles has created challenges for legacy orchestration systems and the ETSI NFV and MEC standards. They were designed for handling virtual machine-based network functions, restricting them in their approach to managing a cloud-native network function. The thesis examines the existing standards of ETSI NFV, ETSI MEC, and network service/slice orchestrators. Aiming to overcome the challenges around multi-domain cloud-native network slice orchestration. To reach the goal, the thesis first proposes MEC Radio Network Information Service (RNIS) that can provide radio information at the subscriber level in an NFV environment. Second, it provides a Dynamic Resource Allocation and Placement (DRAP) algorithm to place cloud-native network services considering their cost and availability matrix. Third, by combining NFV, MEC, and Network Slicing, the thesis proposes a novel Lightweight edge Slice Orchestration framework to overcome the challenges around edge slice orchestration. Fourth, the proposed framework offers an edge slice deployment template that allows multiple possibilities for designing MEC applications. These possibilities were further studied to understand the impact of the microservice design architecture on application availability and latency. Finally, all this work is combined to propose a novel Cloud-native Lightweight Slice Orchestration (CLiSO) framework extending the previously proposed Lightweight edge Slice Orchestration (LeSO) framework. In addition, the framework offers a technology-agnostic and deployment-oriented network slice template. The framework has been thoroughly evaluated via orchestrating OpenAirInterface container network functions on public and private cloud platforms. The experimental results show that the framework has lower resource footprints than existing orchestrators and takes less time to orchestrate network slices
Matoussi, Salma. "User-Centric Slicing with Functional Splits in 5G Cloud-RAN." Electronic Thesis or Diss., Sorbonne université, 2021. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2021SORUS004.pdf.
Full text5G Radio Access Network (RAN) aims to evolve new technologies spanning the Cloud infrastructure, virtualization techniques and Software Defined Network capabilities. Advanced solutions are introduced to split the RAN functions between centralized and distributed locations to improve the RAN flexibility. However, one of the major concerns is to efficiently allocate RAN resources, while supporting heterogeneous 5G service requirements. In this thesis, we address the problematic of the user-centric RAN slice provisioning, within a Cloud RAN infrastructure enabling flexible functional splits. Our research aims to jointly meet the end users’ requirements, while minimizing the deployment cost. The problem is NP-hard. To overcome the great complexity involved, we propose a number of heuristic provisioning strategies and we tackle the problem on four stages. First, we propose a new implementation of a cost efficient C-RAN architecture, enabling on-demand deployment of RAN resources, denoted by AgilRAN. Second, we consider the network function placement sub-problem and propound a new scalable user-centric functional split selection strategy named SPLIT-HPSO. Third, we integrate the radio resource allocation scheme in the functional split selection optimization approach. To do so, we propose a new heuristic based on Swarm Particle Optimization and Dijkstra approaches, so called E2E-USA. In the fourth stage, we consider a deep learning based approach for user-centric RAN Slice Allocation scheme, so called DL-USA, to operate in real-time. The results obtained prove the efficiency of our proposed strategies