Gotowa bibliografia na temat „Slicing du réseau”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Spis treści
Zobacz listy aktualnych artykułów, książek, rozpraw, streszczeń i innych źródeł naukowych na temat „Slicing du réseau”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Rozprawy doktorskie na temat "Slicing du réseau"
Chang, Chia-Yu. "Cloudification and Slicing in 5G Radio Access Network". Electronic Thesis or Diss., Sorbonne université, 2018. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2018SORUS293.pdf.
Pełny tekst źródłaOver the past few decades, the continuing growth of network statistics requires a constantly evolving technology. Therefore, a natural question arises in our minds: what will 5G be? To answer this question, the 5G architecture must be designed with a certain level of flexibility through the integration of softwarization and virtualization principles. Therefore, we can see that 5G will provide a paradigm shift beyond radio access technology in order to establish an agile and sophisticated communication system. The network can be used efficiently and independently by creating multiple logically separated spaces, called network slices. In addition, each logical network can deploy its network functions in a flexible cloud environment. To this end, the goal of this thesis is to study these two techniques: (a) Cloud-RAN and (b) RAN splitting. In the first part, our focus is on the C-RAN concept, in which monolithic base stations are replaced by (1) distributed radio elements and (2) centralized pools for baseband processing units. The C-RAN notion is still confronted with stringent capacity and latency requirements of the fronthaul interface that connects the distributed remote radio unit to the centralized baseband processing unit. In the second part, we focus on RAN cutting not only to allow different levels of isolation and sharing at each slice of network, but also to customize the control plane, user plane and control logic. Therefore, we provide a flexible runtime environment for the "RAN Runtime" slicing system to host service instances on each of the underlying RAN modules
Javel, Aymeric de. "5G RAN : implémentation de la couche physique et découpage du réseau". Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAT031.
Pełny tekst źródłaA critical evolution from 4G to 5G is the heterogeneity of the terminals that connect the network. Those terminals range from smartphones to connected vehicles and sensors for agriculture. Given that the constraints and requirements associated with the different kinds of terminals are heterogeneous, it is not trivial to multiplex the services associated with them on top of a single physical infrastructure. Network slicing is the technology that enables the physical infrastructure to provide multiple logical networks (called network slices) to serve the various devices and associated services: this thesis studies network slicing and its implementation at the RAN level.One main issue raised by network slicing is resource allocation. Indeed, many models exist for resource allocation of the RAN but we are missing models which take into account new constraints implied by network slicing. The first contribution of this thesis is to define a new model for network slicing at the RAN level. This model takes into account diverse slices constraints such as capacity, UEs density, latency, and reliability. Simplicial homology is used to validate slices constraints fulfillment. Furthermore, this model is applied to power optimization, which is a critical aspect of network deployment. The second challenge addressed in this work is the network's supervision and control. Indeed, some verticals have ultra-high control requirements, and the network itself might not be able to satisfy this constraint fully. Therefore, we introduce a probe that can extract data from the network to feed supervision tools for the network's monitoring and control. This probe is designed to be resilient to cyber-attacks and is thus independent of the network.The last main contribution of this thesis is the introduction of an open-source 5G physical layer called free5GRAN. The physical layer provides all the minimal procedures and algorithms for communications between the gNodeB and UEs. The project's structure is built so one can easily modify it and implement new features. Furthermore, the software architecture is designed so that the physical layer is modular and can be derived to implement the open-RAN split 7.2
Bakri, Sihem. "Towards enforcing network slicing in 5G networks". Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS067.
Pełny tekst źródłaThe current architecture “one size fits all” of 4G network cannot support the next-generation 5G heterogeneous services criteria. Therefore, research around 5G aims to provide more adequate architectures and mechanisms to deal with this purpose. The 5G architecture is envisioned to accommodate the diverse and conflicting demands of services in terms of latency, bandwidth, and reliability, which cannot be sustained by the same network infrastructure. In this context, network slicing provided by network virtualization allows the infrastructure to be divided into different slices. Each slice is tailored to meet specific service requirements allowing different services (such as automotive, Internet of Things, etc.) to be provided by different network slice instances. Each of these instances consists of a set of virtual network functions that run on the same infrastructure with specially adapted orchestration. Three main service classes of network slicing have been defined by the researchers as follows: Enhanced Mobile Broadband (eMBB), massive Machine Type Communication (mMTC), and ultra-Reliable and Low-Latency Communication (uRLLC). One of the main challenges when it comes to deploying Network Slices is slicing the Radio Access Network (RAN). Indeed, managing RAN resources and sharing them among Network Slices is an increasingly difficult task, which needs to be properly designed. This thesis proposes solutions that aim to improve network performance, and introduce flexibility and greater utilization of network resources by accurately and dynamically provisioning the activated network slices with the appropriate amounts of resources to meet their diverse requirements
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.
Pełny tekst źródła5G 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
Boutiba, Karim. "On enforcing Network Slicing in the new generation of Radio Access Networks". Electronic Thesis or Diss., Sorbonne université, 2024. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2024SORUS003.pdf.
Pełny tekst źródłaThe emerging 5G networks and beyond promise to support novel use cases such as immersive holographic communication, Internet of Skills, and 4D Interactive mapping [usecases]. These use cases require stringent requirements in terms of Quality of Service (QoS), such as low latency, high Downlink (DL)/Uplink (UL) throughput and low energy consumption. The 3rd Generation Partnership Project (3GPP) specifications introduced many features in 5G New Radio (NR) to improve the physical efficiency of 5G to meet the stringent and heterogeneous requirements of beyond 5G services. Among the key 5G NR features, we can mention the numerology, BandWidth Part (BWP), dynamic Time Duplex Division (TDD) and Connected-mode Discontinuous Reception (C-DRX). However, the specifications do not provide how to configure the next Generation Node B (gNB)/User Equipment (UE) in order to optimize the usage of the 5G NR features. We enforce the 5G NR features by applying Machine Learning (ML), particularly Deep Reinforcement Learning (DRL), to fill this gap. Indeed, Artificial Intelligence (AI)/ML is playing a vital role in communications and networking [1] thanks to its ability to provide a self-configuring and self-optimizing network.In this thesis, different solutions are proposed to enable intelligent configuration of the Radio Access Network (RAN). We divided the solutions into three different parts. The first part concerns RAN slicing leveraging numerology and BWPs. In contrast, the second part tackles dynamic TDD, and the last part goes through different RAN optimizations to support Ultra-Reliable and Low-Latency Communication (URLLC) services.In the first part, we propose two contributions. First, we introduce NRflex, a RAN slicing framework aligned with Open RAN (O-RAN) architecture. NRflex dynamically assigns BWPs to the running slices and their associated User Equipment (UE) to fulfill the slices' required QoS. Then, we model the RAN slicing problem as a Mixed-Integer Linear Programming (MILP) problem. To our best knowledge, this is the first MILP modeling of the radio resource management featuring network slicing, taking into account (i) Mixed-numerology, (ii) both latency and throughput requirements (iii) multiple slices attach per UE (iv) Inter-Numerology Interference (INI). After showing that solving the problem takes an exponential time, we consider a new approach in a polynomial time, which is highly required when scheduling radio resources. The new approach consists of formalizing this problem using a DRL-based solver.In the second part of this thesis, we propose a DRL-based solution to enable dynamic TDD in a single 5G NR cell. The solution is implemented in OAI and tested using real UEs. Then, we extend the solution by leveraging Multi-Agent Deep Reinforcement Learning (MADRL) to support multiple cells, considering cross-link interference between cells.In the last part, we propose three solutions to optimize the RAN to support URLLC services. First, we propose a two-step ML-based solution to predict Radio Link Failure (RLF). We combine Long Short-Term Memory (LSTM) and Support Vector Machine (SVM) to find the correlation between radio measurements and RLF. The RLF prediction model was trained with real data obtained from a 5G testbed. In the second contribution, we propose a DRL-based solution to reduce UL latency. Our solution dynamically allocates the future UL grant by learning from the dynamic traffic pattern. In the last contribution, we introduce a DRL-based solution to balance latency and energy consumption by jointly deriving the C-DRX parameters and the BWP configuration
Biallach, Hanane. "Optimization of VNF reconfiguration problem for 5G network slicing". Electronic Thesis or Diss., Compiègne, 2022. http://www.theses.fr/2022COMP2707.
Pełny tekst źródłaIn recent years, because of the unprecedented growth in the number of connected devices and mobile data, and the ongoing developments in technologies to address this enormous data demand, the fifth generation (5G) network has emerged. The forthcoming 5G architecture will be essentially based on Network Slicing (NS), which enables provide a flexible approach to realize the 5G vision. Thanks to the emerging Network Function Virtualization (NFV) concept, the network functions are decoupled from dedicated hardware devices and realized in the form of software. This offers more flexibility and agility in business operations. Despite the advantages it brings, NFV raises some technical challenges, the reconfiguration problem is one of them. This problem, which is NP-Hard, consists in reallocating the Virtual Network Functions (VNFs) to fit the network changes, by transforming the current state of deployed services, e.g., the current placement of Virtual Machines (VM) that host VNFs, to another state that updates providers’ objectives. This PhD thesis investigates how to reconfigure the VNFs by migrating them to an optimal state that could be computed in advance or free placement. In this thesis, we studied both cases while minimizing the service interruption duration and the VNF migration duration. We have proposed exact and approximate methods. Among the exact methods, we cite two ILP models. We also proposed two heuristic approaches, one based on column generation and the second using the concept of “arc set feedback”. The overall objective of this work is therefore to define and study the problem of VNF reconfiguration problem in the context of 5G network slicing, and propose mathematical models and efficient algorithms to solve the underlying optimization problems
Naddeh, Nathalie. "Impact of slicing on radio resource management in 5G for vehicular URLLC and eMBB". Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAS021.
Pełny tekst źródłaThe Fifth Generation-New Radio (5G-NR) introduced the concept of slicing to target different types of services. We consider in this thesis vehicular traffic, with vehicles sending two types of flows: enhanced Mobile BroadBand (eMBB) and Ultra-Reliable and Low Latency Communications (URLLC). These flows are transported in two different slices, the former trying to guarantee and/or maximize the throughput, while the latter has to meet stringent Quality of Service (QoS) constraints in terms of delay, on the order of 1ms, and reliability, on the order of 99,999%. These slices with heterogeneous traffic profiles and QoS requirements must share the same physical infrastructure. This thesis aims to propose new resource allocation schemes to satisfy URLLC stringent QoS requirements without impacting too much eMBB traffic. One main challenge is when resources initially reserved for eMBB must be allocated to the arrival of new URLLC flow. Due to using different numerologies, these resources need to be reconfigured, adding extra delay on the order of 80ms, which exceeds the URLLC delay budget. To respond to this delay problem, we propose proactive resource reservation schemes for URLLC which anticipates the vehicles' arrival in a cell and (re-)configures the slice before their effective arrival in the cell. These approaches enable to meet the delay and throughput requirements of vehicular URLLC and eMBB traffic, respectively.We additionally introduce an inter-slice dimensioning model that considers user's radio conditions and trajectories in the network, which enables taking into consideration users Modulation and Coding Schemes (MCS). By doing so, we achieve a better resource allocation through finer optimization. Our results show that we are able to satisfy traffic requirements with a better resource utilization.Eventually, we investigate an alternative dimensioning model based on large deviation bounds. We analyze the tail of the system corresponding to the URLLC outage region. We consider two approaches: with and without packet queuing. We observe that large deviation bounds result in slightly more over-reservation than the aforementioned approach when applied to URLLC, with the advantage of instantaneous computation of the needed resources
Foroughi, Parisa. "Towards network automation : planning and monitoring". Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAT038.
Pełny tekst źródłaNetwork management is undergoing drastic changes due to the high expectations of the infrastructure to support new services. The diverse requirements of these services, call for the integration of new enabler technologies that complicate the network monitoring and planning process. Therefore, to alleviate the burden and increase the monitoring and planning accuracy, more automated solutions on the element/device level are required. In this thesis, we propose a semi-automated framework called AI-driven telemetry (ADT) for collecting, processing, and assessing the state of routers using streaming telemetry data. ADT consists of 4 building blocks: collector, detector, explainer, and exporter. We concentrate on the detection block in ADT and propose a multi-variate online change detection technique called DESTIN. Our study on the explainer block of ADT is limited to exploring the potential of the input data and showcasing the possibility of the automated event description. Then, we tackle the problem of planning and dimensioning in radio access networks equipped with distributed edge servers. We propose a model that satisfies the service requirements and makes use of novel enabler technologies, i.e. network slicing and virtualization techniques. We showcase the advantages of using our holistic model to automate RAN planning by utilizing simulated annealing and greedy methods
Esteves, José Jurandir Alves. "Optimization of network slice placement in distributed large-scale infrastructures : from heuristics to controlled deep reinforcement learning". Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS325.
Pełny tekst źródłaThis PhD thesis investigates how to optimize Network Slice Placement in distributed large-scale infrastructures focusing on online heuristic and Deep Reinforcement Learning (DRL) based approaches. First, we rely on Integer Linear Programming (ILP) to propose a data model for enabling on-Edge and on-Network Slice Placement. In contrary to most studies related to placement in the NFV context, the proposed ILP model considers complex Network Slice topologies and pays special attention to the geographic location of Network Slice Users and its impact on the End-to-End (E2E) latency. Extensive numerical experiments show the relevance of taking into account the user location constraints. Then, we rely on an approach called the “Power of Two Choices"(P2C) to propose an online heuristic algorithm for the problem which is adapted to support placement on large-scale distributed infrastructures while integrating Edge-specific constraints. The evaluation results show the good performance of the heuristic that solves the problem in few seconds under a large-scale scenario. The heuristic also improves the acceptance ratio of Network Slice Placement Requests when compared against a deterministic online ILP-based solution. Finally, we investigate the use of ML methods, more specifically DRL, for increasing scalability and automation of Network Slice Placement considering a multi-objective optimization approach to the problem. We first propose a DRL algorithm for Network Slice Placement which relies on the Advantage Actor Critic algorithm for fast learning, and Graph Convolutional Networks for feature extraction automation. Then, we propose an approach we call Heuristically Assisted Deep Reinforcement Learning (HA-DRL), which uses heuristics to control the learning and execution of the DRL agent. We evaluate this solution trough simulations under stationary, cycle-stationary and non-stationary network load conditions. The evaluation results show that heuristic control is an efficient way of speeding up the learning process of DRL, achieving a substantial gain in resource utilization, reducing performance degradation, and is more reliable under unpredictable changes in network load than non-controlled DRL algorithms
Mouawad, Nadia. "SDN based Mobility Management and Quality of Service Provisioning for 5G Vehicular Networks". Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASV003.
Pełny tekst źródłaVehicle to everything (V2X), including vehicle-to-vehicle (V2V) and vehicle-to-infrastructure(V2I), is the umbrella for the vehicular communication system, where active road safety, infotainment and traffic management messages are transmitted over high-bandwidth, low-latency, high-reliability links, paving the way to fully autonomous driving. The ultimate objective of next generation V2X communication systems is enabling accident-free cooperative driving that uses the available roadway efficiently. To achieve this goal, the communication system will need to enable a diverse set of use cases, each with a specific set of requirements.The main use case categories requirements analysis, specifically the critical realtime applications, points out the need for an efficient V2X system design that could fulfill the network performance. The Fifth Generation (5G) technology, with its provisioned QoS features in terms of high capacity and low latency, is advocated as a prominent solution to cope with the firm requirements imposed by V2X applications.In this multifaceted vehicular 5G ecosystem, diverse communication technologies are envisioned, spanning from IEEE 802.11p, LTE, LTE-V to vehicular visible light communications. Therefore, the heterogeneity of radio access technologies will raise a concern regarding the seamless mobility management and the quality of service guarantee.This thesis provides a novel mobility management scheme devised for 5G vehicular networks based on the emerging Software Defined Networking (SDN) technology.SDN provides network programmability that strives to achieve an efficient network resource allocation and mobility management.Our research work tackles three objectives. At a first stage, we design a software defined vehicular network topology. On the top of this topology, we implement twoSDN applications, namely Network Selection Application and Mobility Management Application. The proposed architecture is enhanced by a controller placement solution that aims at reducing communication latency. Moreover, a special concern is devoted to design a SDN road active safety application that controls speed traps placement. The proposed application aims at reducing accidents rate which is a main purpose of future Intelligent Transportation System.The second objective of this thesis tackles the mobility management problem. This is achieved by implementing SDN mobility related applications on the top of the adopted network topology. The first application is dedicated to solve the network selection problem; it aims at mapping running V2X sessions to the corresponding technology. The second application is conceived to solve the handover procedure; this is achieved using packets duplication and introducing an efficient routing algorithm.The third thesis objective is focused on QoS provisioning for V2X communications
Części książek na temat "Slicing du réseau"
HADDADOU, Kamel, i Guy PUJOLLE. "Cloud et Edge Networking des opérateurs". W Cloud et Edge Networking, 135–48. ISTE Group, 2024. http://dx.doi.org/10.51926/iste.9128.ch8.
Pełny tekst źródła