Tesis sobre el tema "Network slicing in 5G"

Les architectures de réseaux sans fil actuelles, de type « une taille pour tous », ne peuvent pas prendre en charge ces critères de services hétérogènes de nouvelle génération 5G. Par conséquent, la recherche autour de la 5G vise à fournir des architectures et des mécanismes plus adéquats pour répondre à ce besoin. L'architecture 5G est conçue pour répondre aux exigences variées et contradictoires des services, en termes de latence, de bande passante et de fiabilité, qui ne peuvent être assurées par la même infrastructure du réseau. Dans ce contexte, le découpage du réseau fourni par la virtualisation du réseau permet de diviser l'infrastructure en différentes tranches, chaque tranche est adaptée aux besoins spécifiques des services, où elle permet à différents services (comme l'automobile, l'Internet des objets...) d'être fournis par différentes instances de la tranche du réseau. Les chercheurs ont défini trois grandes classes de services de découpage en réseau, qui sont: enhanced Mobile BroadBand (eMBB), massive Machine Type Communication (mMTC), and ultra-Reliable and Low-Latency Communication (uRLLC). L'un des principaux défis du déploiement des tranches de réseau est le découpage du réseau d'accès radio (RAN). En effet, la gestion des ressources RAN et leur partage entre les tranches de réseau est une tâche particulièrement difficile. Cette thèse propose des solutions qui visent à améliorer les performances du réseau et d'introduire de la flexibilité et une plus grande utilisation des ressources du réseau, en fournissant de manière précise et dynamique aux tranches de réseau activées les quantités de ressources appropriées pour répondre à leurs divers besoins
The 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

Le « network slicing » est la pierre angulaire pour la conception et le déploiement de services de communication à forte valeur ajoutée qui seront supportés par les nouveaux cas d’usage introduits par la nouvelle architecture 5G. Ce document souligne le défi que représente l’isolation des « network slices », et la gestion de sa sécurité en fonction des politiques retenues.Tout d’abord, un nouveau modèle de contrôle d’accès a été créé. Il permet de sécuriser les interactions entre les fonctions réseaux supportées par les systèmes 5G. Ensuite, la gestion des interactions entre les «network slices » a été abordée. On utilise le concept de chaînes de « network slices », qui seront mises en oeuvre après validation des contraintes de sécurité selon la politique choisie. Enfin, une méthode de quantification de l’isolation a été mise au point, permettant de connaître le degré d’isolation d’un service de communication offert via des « network slices». Cela permet aux opérateurs de réseau et aux clients de mesurer le degré d’isolation, puis d’améliorer la configuration des « network slices » afin de le renforcer. Ces éléments établissent un cadre solide contribuant à sécuriser, verticalement, les services de communication d’un réseau 5G et à évaluer le degré de sécurité en ce qui concerne leurs interactions et leur isolation
Network slicing is a cornerstone in the conception and deployment of enriched communication services for the new use cases envisioned and supported by the new 5G architecture.This document makes emphasis on the challenge of the network slicing isolation and security management according to policy. First, a novel access control model was created, that secures the interactions between network functions that reside inside the 5G system. Then, the management of the interactions between network slices was addressed. We coin the concept of network slice chains, which are conceived after security constraint validation according to policy. Lastly, a method to quantify isolation was developed, permitting to find out how well isolated a communication service is, which is offered via network slices. This enables network operators and customers to measure the isolation level and improve the configuration of the network slices so the isolation level can be enhanced. These components establish a solid framework that contributes to secure, vertically, the communication services of a 5G network and assess how secure they are with respect to their interactions and isolation

Au cours des dernières décennies, la croissance des statistiques d’utilisation de réseau exige une technologique évolutive. Une question naturelle surgit dans nos esprits: que sera la 5G? Pour répondre à cette question, l’architecture 5G doit être conçue avec un certain niveau de flexibilité via l’intégration des principes de softwarization et virtualisation. Le réseau peut être utilisé de manière efficace et indépendante via la création de plusieurs espaces séparées logiquement, appelés tranches de réseau. De plus, chaque réseau logique peut déployer ses fonctions de réseau dans un environnement de nuage avec la flexibilité d’exécution. À cette fin, l’objectif de cette thèse est d’étudier ces deux techniques: (a) C-RAN et (b) découpage de RAN. Dans la première partie, nous étudions C-RAN, dans lequel les stations de base monolithiques sont remplacées par (1) les éléments radio distribués et (2) les pools centralisés pour des unités de traitement en bande de base. Le concept C-RAN est toujours confronté à des exigences sévères en matière de capacité et de latence de l’interface fronthaul qui connecte l’unité de radio distante distribuée à l’unité de traitement en bande de base centralisée. Dans la deuxième partie, nous nous concentrons sur le découpage RAN non seulement pour permettre des différents niveaux d’isolation et de partage à chaque tranche de réseau, mais également pour customiser le plan de contrôle, le plan utilisateur et la logique de contrôle de réseau virtualisé. Par conséquent, nous proposons un environnement d’exécution flexible pour le système de slicing, nommé «RAN Runtime» pour héberger les instances de service sur chacun des modules RAN sous-jacents
Over 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

Ces dernières années, en raison de la croissance sans précédent du nombre d'appareils connectés et de données mobiles, et des développements continus des technologies pour répondre à cette énorme demande de données, le réseau de cinquième génération (5G) a émergé. La future architecture 5G sera essentiellement basée sur le Network Slicing (NS), qui permet de fournir une approche flexible pour réaliser la vision 5G. Grâce au concept émergent de virtualisation des fonctions réseau (NFV), les fonctions réseau sont découplées des matériels physiques dédiés et réalisées sous forme de logiciel. Cela offre plus de flexibilité et d'agilité dans les opérations commerciales. Malgré les avantages qu'il apporte, NFV soulève quelques défis techniques, le problème de reconfiguration étant l'un d'entre eux. Ce problème, qui est NP-difficile, consiste à réaffecter les fonctions de réseau virtuel (VNFs) pour s'adapter aux changements du réseau, en transformant l'état courant des services déployés, on peut illustrer cela par la migration des machines virtuelles (VM) qui hébergent les VNF, à un autre état qui répond aux objectives des opérateurs. Cette thèse de doctorat étudie comment reconfigurer les VNFs en les migrant vers un état optimal qui pourrait être calculé en avance ou inconnu. Dans cette thèse, nous avons étudié les deux cas en minimisant la durée d'interruption de service et la durée de migration des VNFs. Nous avons proposé des méthodes exactes et approchées. Parmi les méthodes exactes, nous citons deux modèles PLNE. Nous avons également proposé deux approches heuristiques, l'une basée sur la génération de colonnes et la deuxième utilisant la notion de “feedback arc set". L'objectif global de ce travail est donc de définir et d'étudier le problème de reconfiguration des VNFs dans le contexte du 5G network slicing, et de proposer des modèles mathématiques et des algorithmes efficaces pour résoudre les problèmes d'optimisation sous-jacents
In 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

This thesis deals with the topic of network slicing technology in 5G networks, mainly on the RAN part. In the theoretical part, basic principles of 5G network slicing in core network part and RAN part are presented. Practical part contains a simulation scenario created in NS3 simulator with LENA 5G module. Results of this simulation are presented and discussed with the emphasis on RAN slicing.

La spécification du réseau 5G requiert des propriétés ACID (Atomicity, Consistency, Isolation, Durability) pour sa base de données distribuée. D’après le théorème de CAP, ce niveau de cohérence est incompatible avec un système géo-distribué de haute disponibilité. Les réseaux mobiles étant sujets à des obligations de disponibilité, cette contradiction remet en question la spécification. Notre thèse se concentre sur une étude de l’usage des données dans le réseau qui nous permet d’en extraire des propriétés de cohérence plus faibles que ACID mais suffisantes pour que ces données restent correctes. Dans le cas du Network Slicing, une innovation propre aux réseaux 5G, nous proposons une étude plus approfondie de l’application d’une de ces propriétés, à travers l’exemple d’une limite qui borne globalement l’utilisation des ressources du réseau pour un slice. Les données liées à une slice sont potentiellement largement distribuées, et l’application d’une limite y est donc plus difficile. Nous proposons plusieurs algorithmes placés à différents niveaux de cohérence afin d’étudier leur performance dans une simulation du réseau 5G
The 5G network specification requires ACID properties (Atomicity, Consistency, Isolation, Durability) for its distributed database. According to the CAP theorem, these properties are incompatible with high availability for a geo-distributed system. Since availability is an obligation for mobile networks, this contradiction challenges the specification. Our thesis focus on a study of the usage of data in the network that allow us to extract weaker consistency properties that are still sufficient to maintain the correctness of the data. In the case a Network Slicing, an innovation of the 5G network, we propose to study further the enforcement of one of these properties, through the example of the enforcement of a global limit on the resource usage of a slice. Slices are deployed over a potentially large are, and so is their data, which make the enforcement of a limit more challenging. We propose several algorithms placed at different points of the consistency spectrum and study their performance in a simulation of the 5G network

Le réseau d’accès radio (RAN) 5G vise à faire évoluer de nouvelles technologies couvrant l’infrastructure Cloud, les techniques de virtualisation et le réseau défini par logiciel (SDN). Des solutions avancées sont introduites pour répartir les fonctions du réseau d’accès radio entre des emplacements centralisés et distribués (découpage fonctionnel) afin d’améliorer la flexibilité du RAN. Cependant, l’une des préoccupations majeures est d’allouer efficacement les ressources RAN, tout en prenant en compte les exigences hétérogènes des services 5G. Dans cette thèse, nous abordons la problématique du provisionnement des ressources Cloud RAN centré sur l’utilisateur (appelé tranche d’utilisateurs ). Nous adoptons un déploiement flexible du découpage fonctionnel. Notre recherche vise à répondre conjointement aux besoins des utilisateurs finaux, tout en minimisant le coût de déploiement. Pour surmonter la grande complexité impliquée, nous proposons d’abord une nouvelle implémentation d’une architecture Cloud RAN, permettant le déploiement à la demande des ressources, désignée par AgilRAN. Deuxièmement, nous considérons le sous-problème de placement des fonctions de réseau et proposons une nouvelle stratégie de sélection de découpage fonctionnel centrée sur l’utilisateur nommée SPLIT-HPSO. Troisièmement, nous intégrons l’allocation des ressources radio. Pour ce faire, nous proposons une nouvelle heuristique appelée E2E-USA. Dans la quatrième étape, nous envisageons une approche basée sur l’apprentissage en profondeur pour proposer un schéma d’allocation temps réel des tranches d’utilisateurs, appelé DL-USA. Les résultats obtenus prouvent l’efficacité de nos stratégies proposées
5G 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

The 5th generation of mobile networking introduces the concept of “Network slicing”, the network will be “sliced” horizontally, each slice will be compliant with different requirements in terms of network parameters such as bandwidth, latency. This technology is built on logical instead of physical resources, relies on virtual network as main concept to retrieve a logical resource. The Network Function Virtualisation provides the concept of logical resources for a virtual network function, enabling the concept virtual network; it relies on the Software Defined Networking as main technology to realize the virtual network as resource, it also define the concept of virtual network infrastructure with all components needed to enable the network slicing requirements. SDN itself uses cloud computing technology to realize the virtual network infrastructure, NFV uses also the virtual computing resources to enable the deployment of virtual network function instead of having custom hardware and software for each network function. The key of network slicing is the differentiation of slice in terms of Quality of Services parameters, which relies on the possibility to enable QoS management in cloud computing environment. The QoS in cloud computing denotes level of performances, reliability and availability offered. QoS is fundamental for cloud users, who expect providers to deliver the advertised quality characteristics, and for cloud providers, who need to find the right tradeoff between QoS levels that has possible to offer and operational costs. While QoS properties has received constant attention before the advent of cloud computing, performance heterogeneity and resource isolation mechanisms of cloud platforms have significantly complicated QoS analysis and deploying, prediction, and assurance. This is prompting several researchers to investigate automated QoS management methods that can leverage the high programmability of hardware and software resources in the cloud.

Les réseaux 5G émergents et au-delà promettent de prendre en charge de nouveaux cas d'utilisation tels que la communication holographique immersive, l'internet des compétences et la cartographie interactive 4D [1]. Ces cas d'usage ont des exigences strictes en termes de Quality de Service (Quality of Service), telles qu'une faible latence, un débit descendant et ascendant (Downlink (DL)/Uplink (UL)) élevé, ainsi qu'une faible consommation d'énergie. Les spécifications du groupe de normalisation 3GPP ont introduit de nombreuses fonctionnalités aux système radio 5G (5G NR), dans le but d'améliorer l'efficacité spectrale de la 5G et de répondre aux exigences strictes et hétérogènes des services de la 5G et au-delà. Parmi les principales fonctionnalités de la 5G NR, on peut citer l'introduction du concept de numérologie et BandWidth Part (BWP), le multiplexage temporel (TDD) dynamique et Connected-mode Discontinuous Reception (C-DRX). Toutefois, les spécifications 3GPP n'indiquent pas comment configurer la next gNode B (gNB)/User Equipment (UE) pour optimiser l'utilisation des fonctionnalités 5G NR. Afin de combler ce manque, nous proposons de nouvelles solutions qui mettent en œuvre des fonctionnalités 5G NR en appliquant les techniques de l'apprentissage automatique ou Machine Learning (ML), en particulier l'apprentissage profond par renforcement ou Deep Reinforcement Learning (DRL). En effet, les outils de l'intelligence artificielle jouent un rôle essentiel dans l'optimisation des systèmes de communication et des réseaux [2] grâce à leurs capacités à rendre le réseau capable de s'auto-configurer et s'auto-optimiser.Dans cette thèse, nous proposons plusieurs solutions pour permettre une configuration intelligente du réseau d'accès radio (RAN). Nous avons divisé les solutions en trois parties distinctes.Dans la première partie, nous proposons deux contributions. Tout d'abord, nous présentons NRflex, une solution de découpage du RAN en tranches (ou slicing), aligné sur l'architecture Open RAN (O-RAN). Par la suite, nous modélisons le problème de découpage du RAN en tranches comme un problème Mixed-Integer Linear Programming (MILP). Après avoir montré que la résolution du problème prend un temps exponentiel, nous avons introduit une nouvelle approche pour le résoudre en un temps polynomial, ce qui est très important pour la fonction de l'ordonnancement (scheduling) des ressources radio. La nouvelle approche consiste à formaliser et résoudre ce problème par le biais l'apprentissage par renforcement profond (DRL).Dans la deuxième partie de la thèse, nous proposons une solution basée sur le DRL pour permettre un TDD dynamique dans une seule cellule 5G NR. La solution a été implémentée dans la plateforme OpenAirInterface (OAI) et testée avec UEs réels. Nous avons ensuite étendu la solution, en tirant parti de Multi-Agent Deep Reinforcement Learning (MADRL), pour prendre en charge plusieurs cellules en tenant compte de l'interférence radio entre les liaisons transversales entre les cellules.Dans la dernière partie de la thèse, nous avons proposé trois solutions pour optimiser le RAN afin de prendre en charge les services URLLC. Tout d'abord, nous avons proposé une solution en deux étapes basées sur l'apprentissage automatique pour prédire les coupures du lien radio ou Radio Link Failure (RLF). Le modèle de prédiction RLF a été entraîné avec des données réelles obtenues à partir d'un banc d'essai 5G. Dans la deuxième contribution, nous avons proposé une solution basée sur le DRL pour réduire la latence UL. Notre solution alloue (prédit) dynamiquement les futurs besoins en ressource radio du UL en apprenant du modèle de trafic. Dans la dernière contribution, nous introduisons une solution basée sur le DRL afin d'équilibrer la latence et la consommation d'énergie en calculant conjointement les paramètres C-DRX et la configuration BWP
The 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

Les futurs réseaux mobiles promettent des opportunités sans précédent pour l'innovation et des cas d'utilisation disruptifs. L'engagement des réseaux 5G et au-delà à fournir des applications critiques nécessite un réseau polyvalent, évolutif, efficace et rentable, capable d'adapter son allocation de ressources pour répondre aux exigences de services hétérogènes. Pour relever ces défis, le découpage du réseau s'est imposé comme l'un des concepts fondamentaux proposés pour améliorer l'efficacité des réseaux mobiles 5G et leur conférer la plasticité requise. L'idée est de fournir des ressources à différentes industries verticales en construisant plusieurs réseaux logiques de bout en bout sur une infrastructure virtualisée partagée. Chaque "tranche de réseau" ainsi définie est personnalisée pour fournir un service spécifique en adaptant son architecture et ses technologies d'accès radio.Précisément, des applications telles que l'automatisation industrielle ou les communications entre véhicules imposent aux réseaux cellulaires des exigences strictes en matière de latence et de fiabilité. Étant donné que le réseau mobile actuel ne peut pas répondre à ces exigences, les communications ultra-fiables et à faible temps de latence constituent un sujet de recherche essentiel qui a suscité un élan considérable de la part du monde universitaire et des alliances industrielles. Pour répondre à ces exigences, l'utilisation de la multi-connectivité, c'est-à-dire l'exploitation simultanée de plusieurs liaisons radio comme voies de communication, est une approche prometteuse.L'objectif du présent manuscrit est d'étudier des techniques d'allocation de resources exploitant la couverture redondante des utilisateurs, garantie dans de nombreux scénarios 5G. Nous examinons d'abord l'évolution des réseaux mobiles et discutons des diverses considérations relatives à l'architecture de découpage du réseau et de son impact sur la conception des méthodes d'allocation des ressources. Nous utilisons ensuite les outils de la théorie des files d'attente pour modéliser un système dans lequel un ensemble d'utilisateurs URLLC sont connectés simultanément à deux stations de base ayant la même bande passante ; nous appelons ce scénario le cas homogène. Nous introduisons des politiques d'allocation appropriées et évaluons leurs performances respectives en évaluant leur fiabilité. Ensuite, nous étendons les résultats du cas homogène à un cadre plus général où les interfaces physiques gèrent des bandes passantes différentes, que nous appelons le cas hétérogène. Enfin, nous fusionnons les éléments ci-dessus pour valider le choix des schémas d'allocation des ressources en tenant compte de l'architecture déployée
Future mobile networks envision unprecedented innovation opportunities and disruptive use cases. As a matter of fact, the 5G and beyond networks' pledge to deliver mission-critical applications mandates a versatile, scalable, efficient, and cost-effective network capable of accommodating its resource allocation to meet the services' heterogeneous requirements. To face these challenges, network slicing has emerged as one of the fundamental concepts proposed to raise the 5G mobile networks' efficiency and provide the required plasticity. The idea is to provide resources for different vertical industries by building multiple end-to-end logical networks over a shared virtualized infrastructure. Each network slice is customized to deliver a specific service and adapts its architecture and radio access technologies.Precisely, applications such as industrial automation or vehicular communications pose stringent latency and reliability requirements on cellular networks. Given that the current mobile network cannot meet these requirements, ultra-reliable low-latency communications (URLLC) embodies a vital research topic that has gathered substantial momentum from academia and industrial alliances. To reach URLLC requirements, employing multi-connectivity (MC), i.e., exploiting multiple radio links as communication paths at once, is a promising approach.Therefore, the objective of the present manuscript is to investigate dynamic scheduling techniques, exploiting redundant coverage of users, guaranteed in numerous 5G radio access network scenarios. We first review the evolution of mobile networks and discuss various considerations for network slicing architecture and its impact on resource allocation design. Then, we use tools from queuing theory to model a system in which a set of URLLC users are connected simultaneously to two base stations having the same bandwidth; we refer to this scenario as the homogenous case. We introduce suitable scheduling policies and evaluate their respective performances by assessing their reliability. Next, we extend the homogenous case's results to a more general setting where the physical interfaces manage different bandwidths, referred to as the heterogeneous case. Finally, we merge the above elements to validate the choice of resource allocation schemes considering the deployed architecture

La prolifération d'applications et de services sophistiqués s'accompagne de diverses exigences de performances, ainsi que d'une croissance exponentielle du trafic pour le lien montant (uplink) et descendant (downlink). Les réseaux cellulaires tels que 4G et 5G évoluent pour prendre en charge cette quantité diversifiée et énorme de données. Le travail de cette thèse vise le renforcement de techniques avancées de gestion et supervision des réseaux cellulaires prenant l'explosion du trafic et sa diversité comme deux des principaux défis dans ces réseaux. La première contribution aborde l'intégration de l'intelligence dans les réseaux cellulaires via l'estimation du débit instantané sur le lien montant pour de petites granularités temporelles. Un banc d'essai 4G temps réel est déployé dans ce but de fournir un benchmark exhaustif des métriques de l'eNB. Des estimations précises sont ainsi obtenues. La deuxième contribution renforce le découpage 5G en temps réel au niveau des ressources radio dans un système multicellulaire. Pour cela, deux modèles d'optimisation ont été proposés. Du fait de leurs temps d'exécution trop long, des heuristiques ont été développées et évaluées en comparaisons des modèles optimaux. Les résultats sont prometteurs, les deux heuristiques renforçant fortement le découpage du RAN en temps réel
The proliferation of sophisticated applications and services comes with diverse performance requirements as well as an exponential traffic growth for both upload and download. The cellular networks such as 4G and 5G are advocated to support this diverse and huge amount of data. This thesis work targets the enforcement of advanced cellular network supervision and management techniques taking the traffic explosion and diversity as two main challenges in these networks. The first contribution tackles the intelligence integration in cellular networks through the estimation of users uplink instantaneous throughput at small time granularities. A real time 4G testbed is deployed for such aim with an exhaustive metrics benchmark. Accurate estimations are achieved.The second contribution enforces the real time 5G slicing from radio resources perspective in a multi-cell system. For that, two exact optimization models are proposed. Due to their high convergence time, heuristics are developed and evaluated with the optimal models. Results are promising, as two heuristics are highly enforcing the real time RAN slicing

La virtualisation des fonctions réseau (NFV) est le pilier fondateur de l'architecture 5G basée sur les services. La NFV a débuté en 2012, avec les fonctions de réseau virtuelles (VNF) basées sur les machines virtuelles (VM). Les conteneurs sont devenus une technologie alternative de conditionnement intéressante pour la virtualisation des fonctions réseau. Le conteneur est léger en termes de consommation de ressources ce qui améliore son temps d'instanciation. Outre les fonctions de réseau, la conteneurisation peut être un outil prometteur pour les applications multi-access edge computing (MEC) qui abritent des services exigeants à faible latence. La rareté des ressources à la périphérie du réseau exige des technologies qui utilisent efficacement les ressources de calcul, de stockage et de mise en réseau. La conteneurisation est censée être utilisée dans le cadre des principes fondamentaux de la conception d'applications cloud-native, une architecture basée sur des microservices à couplage lâche, d'une évolutivité à la demande et d'une résilience élevée. La flexibilité et l'agilité des conteneurs peuvent certainement profiter au découpage du réseau 5G en tranches,ces derniers reposent fortement sur NFV et MEC. Le concept de découpage du réseau permet de créer des réseaux logiques isolés au-dessus du même réseau physique. Une tranche de réseau peut avoir des fonctions de réseau dédiées, partagées entre plusieurs tranches. En effet, l'orchestration des tranches de réseau nécessite une interaction avec de multiples orchestrateurs de domaines technologiques: l'accès radio, le transport, le réseau central et l'informatique périphérique. Le changement de paradigme consistant à utiliser des principes de conception d'applications cloud-natives a créé des défis pour les systèmes d'orchestration existants et les normes NFV et MEC de l'ETSI. Ces derniers ont été conçus pour gérer des fonctions de réseau basées sur des machines virtuelles. Ils sont donc limités dans leur approche de la gestion d'une fonction de réseau cloud-native. Par le présent manuscrit, nous examinons les normes existantes de l'ETSI NFV, de l'ETSI MEC et des orchestrateurs de services/tranches de réseau, nous proposons de résoudre les défis liés à l'orchestration de tranches de réseau multi-domaines cloud-native. Pour cela, nous proposons tout d'abord un service d'information sur le réseau radio (RNIS) MEC qui a la capacité de fournir des informations radio au niveau de l'abonné dans un environnement NFV. Deuxièmement, nous fournissons un algorithme d'allocation et de placement dynamique des ressources (DRAP) pour placer les services réseau cloud-natives en tenant compte de leur matrice de coût et de disponibilité. Troisièmement, en combinant NFV, MEC et Network Slicing, nous proposons un nouveau mécanisme d'orchestration de tranches MEC (LeSO) pour surmonter les défis liés à l'orchestration de tranches MEC. Quatrièmement, le mécanisme proposé offre un modèle de déploiement de tranches de réseau qui permet de multiples possibilités de conception d'applications MEC. Ces possibilités ont été étudiées plus en détails pour comprendre l'impact de l'architecture de conception microservice sur la disponibilité et la latence de l'application. Enfin, tous ces travaux sont combinés pour proposer une nouvelle approche d'orchestration de tranches légères Cloud-native (CLiSO) étendant le précédant mécanisme d'orchestration de tranches légères de bord (LeSO). Cette nouvelle approche offre un modèle de tranche de réseau agnostique sur le plan technologique et orienté déploiement. La solution a été évaluée de manière approfondie en orchestrant les fonctions réseau du conteneur OpenAirInterface sur des plateformes de cloud public et privé. Les résultats expérimentaux montrent que la solution proposée a des empreintes de ressources plus faibles que les orchestrateurs existants et prend moins de temps pour orchestrer les tranches de réseau
Network 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

Gli obiettivi posti dalle nuove generazione di rete sono molto più ambiziosi rispetto al passato e pongono degli ostacoli che possono essere superati solamente adottando un'architettura più evoluta e dei paradigmi per la sua progettazione che consentono di agevolarne la gestione, aumentarne la flessibilità e scalabilità. Le reti mobili attuali, ed in particolare l'infrastruttura sottostante che ne consente il funzionamento, sono costituite da apparecchi hardware dedicati, spesso vincolati a vendor specifici, opportunamente configurati; tali caratteristiche rendono l'architettura rigida, complessa da manutenere e quindi costosa. La volontà di staccarsi da questi vincoli ha portato il mondo delle telecomunicazioni, così come quello dell'informatica ad approcciarsi al cloud ed architetture orientate ai servizi. Il cuore dell'architettura 5G è costituito da un insieme di componenti, in grado di comunicare e/o cooperare con altri componenti mediante apposite interfacce. I paradigmi adottati introducono la possibilità di programmare via software la rete e le sue funzionalità, svincolandosi dal limiti fisici delle apparecchiature hardware che le erogano, agevolandone la progettazione, l'implementazione e la gestione. Le tecnologie di virtualizzazione odierne ci consentono di effettuare il deployment dei servizi di rete in modo agevole; tali servizi inoltre, possono essere orchestrati tramite appositi framework che ne semplificano la gestione ed il dispiegamento automatizzato.

Les réseaux 5G sont envisagés comme un changement de paradigme vers des réseaux orientés services. Dans cette thèse, nous étudions comment combiner efficacement le découpage en tranches et le SD-RAN afin de fournir le niveau requis de flexibilité et de programmabilité dans l'infrastructure RAN pour réaliser des réseaux multi-locataires orientés services. Premièrement, nous concevons une abstraction d'une station de base pour représenter les stations de base logiques et décrire un service de réseau virtualisé. Deuxièmement, nous proposons une nouvelle plateforme SD-RAN conforme aux normes, appelée FlexRIC, sous la forme d'un kit de développement logiciel (SDK). Troisièmement, nous fournissons une conception modulaire pour un cadre d'ordonnancement MAC tenant compte des tranches afin de gérer et de contrôler efficacement les ressources radio dans un environnement multiservice avec un support de qualité de service (QoS). Enfin, nous présentons une couche de virtualisation SD-RAN dynamique basée sur le SDK FlexRIC et le cadre d'ordonnancement MAC pour composer de manière flexible une infrastructure SD-RAN multiservice et fournir une programmabilité pour de multiples contrôleurs SD-RAN
5G networks are envisioned to be a paradigm shift towards service-oriented networks. In this thesis, we investigate how to efficiently combine slicing and SD-RAN to provide the required level of flexibility and programmability in the RAN infrastructure to realize service-oriented multi-tenant networks. First, we devise an abstraction of a base station to represent logical base stations and describe a virtualized network service. Second, we propose a novel standard-compliant SD-RAN platform, named FlexRIC, in the form of a software development kit (SDK). Third, we provide a modular design for a slice-aware MAC scheduling framework to efficiently manage and control the radio resources in a multi-service environment with quality-of-service (QoS) support. Finally, we present a dynamic SD-RAN virtualization layer based on the FlexRIC SDK and MAC scheduling framework to flexibly compose a multi-service SD-RAN infrastructure and provide programmability for multiple SD-RAN controllers

With the advent of 5G, telecommunications are undergoing unprecedented changes. Network architectures are evolving to support new business models and services. The transition to 5G encompasses many technological aspects and design processes. The new generation system focuses on bringing an overall performance improvement in terms of latency and throughput, as well as on exibility and scalability of the infrastructure. Network Slicing plays a key role in the aforementioned transition, allowing to build different logical networks on top of the same common infrastructure. Moreover, the evolution of the core network is a key aspect as well for the integration of new functionalities and to enable full 5G capabilities. In this regard, the core network needs to move from the current complex, cost-inefficient infrastructure to a more dynamic architecture. This can be achieved by leveraging virtualization technologies supporting paradigms including Network Function Virtualization (NFV), Software Defined Networking (SDN) and Cloud Computing, which are considered key enablers for 5G. This thesis focuses on the orchestration of a virtualized mobile core network, starting from the modelling of MANO descriptors and moving to the deployment in a multi-domain cloud scenario. In particular, the objective of the activity is to highlight methodologies and problems relevant to that deployment, including the configuration of all the involved elements and available software solutions. For the implementation, Open Source MANO (OSM) is used as management and orchestration platform, and OpenStack as cloud platform and Virtualized Infrastructure Manager (VIM). Moreover, the NextEPC software suite is utilized to implement the core network elements whereas eNodeB and UEs are simulated with the L2 nFAPI software provided by OpenAirInterface.

Network slicing provides a scalable and flexible solution for resource allocation with performance guaranty and isolation from other services in the 5G architecture. 5G has to handle several active use cases with different requirements. The single solution to satisfy all the extreme requirements requires overspecifies and high-cost network architecture. Further, to fulfill the diverse requirements, each service will require different resources from a radio access network (RAN), edge, and central offices of 5G architecture and hence various deployment options. Network function virtualization allocates radio access network (RAN) functions in different nodes. URLLC services require function placement nearer to the ran to fulfill the lower latency requirement while eMBB require cloud access for implementation. Therefore arbitrary allocation of network function for different services is not possible. We aim to developed algorithms to find service-based placement for RAN functions in a multitenant environment with heterogeneous demands. We considered three generic classes of slices of eMBB, URLLC, mMTC. Every slice is characterized by some specific requirements, while the nodes and the links are resources constrained. The function placement problem corresponds to minimize the overall cost of allocating the different functions to the different nodes organized in layers for respecting the requirements of the given slices. Specifically, we proposed three algorithms based on the normalized preference associated with each slice on different layers of RAN architecture. The maximum preference algorithm places the functions on the most preferred position defined in the preference matrix. On the other hand, the proposed modified preference algorithm provides solutions by keeping track of the availability of computational resources and latency requirements of different services. We also used the Exhaustive Search Method for solving a function allocation problem.

Vehicle to Everything (V2X), y compris véhicule à véhicule (V2V) et véhicule à infrastructure (V2I), est la base de communications véhiculaires, où Les messages de sécurité routière active, d’infotainment et de gestion du trafic sont transmis sur des liaisons à bande passante élevée, à faible temps de latence et à haute fiabilité, ouvrant ainsi la voie à une conduite totalement autonome. L’objectif ultime des systèmes de communication V2X de la prochaine génération est de permettre une conduite coopérative sans accident. Pour atteindre cet objectif, le système de communication devra permettre un ensemble diversifié de cas d'usage, chacun avec un ensemble spécifique d'exigences. L'analyse des exigences relatives aux principales catégories de cas d’usage, en particulier les applications de temps réel critiques, souligne la nécessité d'une conception de système V2X efficace, capable de fournir les performances du réseau. La technologie de cinquième génération (5G), avec sa Qualité de Service (QoS) fournie en termes de capacité élevée et de faible temps de latence, est préconisée comme solution pour faire face aux exigences strictes imposées par les applications V2X.Dans cet écosystème 5G véhiculaire, diverses technologies de communication sont envisagés, allant des communications IEEE 802.11p, LTE, LTE-V aux Visible Light Communications. Par conséquent, l’hétérogénéité des technologies d’accès radio suscitera des inquiétudes quant à la gestion transparente de la mobilité et à la garantie de qualité de service.Cette thèse propose un nouveau système de gestion de la mobilité conçu pour les réseaux de véhicules 5G, basé sur la technologie émergente SDN (Software Defined Networking). SDN offre une programmabilité réseau qui vise à obtenir une allocation efficace des ressources du réseau et une gestion de la mobilité.Notre travail de recherche vise trois objectifs. Dans un premier temps, nous concevons une architecture de réseau de véhicules. Au sommet de cette architecture, nous implémentons deux Applications SDN, à savoir application de sélection de réseau et gestion de la mobilité Application. L'architecture proposée est renforcée par une solution de placement de contrôleur visant à réduire le temps de latence des communications. De plus, une préoccupation particulière est consacrée à la conception d’une application de sécurité active de la route SDN contrôlant l’emplacement des capteurs de vitesse sur les routes. L’application proposée vise à réduire le taux d’accidents, objectif principal du futur système de transport intelligent.Le deuxième objectif de cette thèse aborde le problème de la gestion de la mobilité.Ceci est réalisé en implémentant des applications liées à la mobilité SDN au sommet de la topologie de réseau adoptée. La première application est dédiée à la résolution du problème de sélection du réseau. Son objectif est de mapper les sessions V2X en cours sur la technologie correspondante. La deuxième application est conçue pour résoudre le handover; ceci est réalisé en utilisant la duplication de paquets et en introduisant un algorithme de routage efficace.Le troisième objectif de la thèse est axé sur l’approvisionnement en qualité de service pour les communications V2X
Vehicle 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

Telecom operators networks' management and control remains partitioned by technology, equipment supplier and networking layer. In some segments, the network operations are highly costly due to the need of the individual, and even manual, configuration of the network equipment by highly specialized personnel. In multi-vendor networks, expensive and never ending integration processes between Network Management Systems (NMSs) and the rest of systems (OSSs, BSSs) is a common situation, due to lack of adoption of standard interfaces in the management systems of the different equipment suppliers. Moreover, the increasing impact of the new traffic flows introduced by the deployment of massive Data Centers (DCs) is also imposing new challenges that traditional networking is not ready to overcome. The Fifth Generation of Mobile Technology (5G) is also introducing stringent network requirements such as the need of connecting to the network billions of new devices in IoT paradigm, new ultra-low latency applications (i.e., remote surgery) and vehicular communications. All these new services, together with enhanced broadband network access, are supposed to be delivered over the same network infrastructure. In this PhD Thesis, an holistic view of Network and Cloud Computing resources, based on the recent innovations introduced by Software Defined Networking (SDN), is proposed as the solution for designing an end-to-end multi-layer, multi-technology and multi-domain cloud and transport network management architecture, capable to offer end-to-end services from the DC networks to customers access networks and the virtualization of network resources, allowing new ways of slicing the network resources for the forthcoming 5G deployments. The first contribution of this PhD Thesis deals with the design and validation of SDN based network orchestration architectures capable to improve the current solutions for the management and control of multi-layer, multi-domain backbone transport networks. These problems have been assessed and progressively solved by different control and management architectures which has been designed and evaluated in real evaluation environments. One of the major findings of this work has been the need of developed a common information model for transport network's management, capable to describe the resources and services of multilayer networks. In this line, the Control Orchestration Protocol (COP) has been proposed as a first contriution towards an standard management interface based on the main principles driven by SDN. Furthermore, this PhD Thesis introduces a novel architecture capable to coordinate the management of IT computing resources together with inter- and intra-DC networks. The provisioning and migration of virtual machines together with the dynamic reconfiguration of the network has been successfully demonstrated in a feasible timescale. Moreover, a resource optimization engine is introduced in the architecture to introduce optimization algorithms capable to solve allocation problems such the optimal deployment of Virtual Machine Graphs over different DCs locations minimizing the inter-DC network resources allocation. A baseline blocking probability results over different network loads are also presented. The third major contribution is the result of the previous two. With a converged cloud and network infrastructure controlled and operated jointly, the holistic view of the network allows the on-demand provisioning of network slices consisting of dedicated network and cloud resources over a distributed DC infrastructure interconnected by an optical transport network. The last chapters of this thesis discuss the management and orchestration of 5G slices based over the control and management components designed in the previous chapters. The design of one of the first network slicing architectures and the deployment of a 5G network slice in a real Testbed, is one of the major contributions of this PhD Thesis.
La gestión y el control de las redes de los operadores de red (Telcos), todavía hoy, está segmentado por tecnología, por proveedor de equipamiento y por capa de red. En algunos segmentos (por ejemplo en IP) la operación de la red es tremendamente costosa, ya que en muchos casos aún se requiere con guración individual, e incluso manual, de los equipos por parte de personal altamente especializado. En redes con múltiples proveedores, los procesos de integración entre los sistemas de gestión de red (NMS) y el resto de sistemas (p. ej., OSS/BSS) son habitualmente largos y extremadamente costosos debido a la falta de adopción de interfaces estándar por parte de los diferentes proveedores de red. Además, el impacto creciente en las redes de transporte de los nuevos flujos de tráfico introducidos por el despliegue masivo de Data Centers (DC), introduce nuevos desafíos que las arquitecturas de gestión y control de las redes tradicionales no están preparadas para afrontar. La quinta generación de tecnología móvil (5G) introduce nuevos requisitos de red, como la necesidad de conectar a la red billones de dispositivos nuevos (Internet de las cosas - IoT), aplicaciones de ultra baja latencia (p. ej., cirugía a distancia) y las comunicaciones vehiculares. Todos estos servicios, junto con un acceso mejorado a la red de banda ancha, deberán ser proporcionados a través de la misma infraestructura de red. Esta tesis doctoral propone una visión holística de los recursos de red y cloud, basada en los principios introducidos por Software Defined Networking (SDN), como la solución para el diseño de una arquitectura de gestión extremo a extremo (E2E) para escenarios de red multi-capa y multi-dominio, capaz de ofrecer servicios de E2E, desde las redes intra-DC hasta las redes de acceso, y ofrecer ademas virtualización de los recursos de la red, permitiendo nuevas formas de segmentación en las redes de transporte y la infrastructura de cloud, para los próximos despliegues de 5G. La primera contribución de esta tesis consiste en la validación de arquitecturas de orquestración de red, basadas en SDN, para la gestión y control de redes de transporte troncales multi-dominio y multi-capa. Estos problemas (gestion de redes multi-capa y multi-dominio), han sido evaluados de manera incremental, mediante el diseño y la evaluación experimental, en entornos de pruebas reales, de diferentes arquitecturas de control y gestión. Uno de los principales hallazgos de este trabajo ha sido la necesidad de un modelo de información común para las interfaces de gestión entre entidades de control SDN. En esta línea, el Protocolo de Control Orchestration (COP) ha sido propuesto como interfaz de gestión de red estándar para redes SDN de transporte multi-capa. Además, en esta tesis presentamos una arquitectura capaz de coordinar la gestión de los recursos IT y red. La provisión y la migración de máquinas virtuales junto con la reconfiguración dinámica de la red, han sido demostradas con éxito en una escala de tiempo factible. Además, la arquitectura incorpora una plataforma para la ejecución de algoritmos de optimización de recursos capaces de resolver diferentes problemas de asignación, como el despliegue óptimo de Grafos de Máquinas Virtuales (VMG) en diferentes DCs que minimizan la asignación de recursos de red. Esta tesis propone una solución para este problema, que ha sido evaluada en terminos de probabilidad de bloqueo para diferentes cargas de red. La tercera contribución es el resultado de las dos anteriores. La arquitectura integrada de red y cloud presentada permite la creación bajo demanda de "network slices", que consisten en sub-conjuntos de recursos de red y cloud dedicados para diferentes clientes sobre una infraestructura común. El diseño de una de las primeras arquitecturas de "network slicing" y el despliegue de un "slice" de red 5G totalmente operativo en un Testbed real, es una de las principales contribuciones de esta tesis.
La gestió i el control de les xarxes dels operadors de telecomunicacions (Telcos), encara avui, està segmentat per tecnologia, per proveïdors d’equipament i per capes de xarxa. En alguns segments (Per exemple en IP) l’operació de la xarxa és tremendament costosa, ja que en molts casos encara es requereix de configuració individual, i fins i tot manual, dels equips per part de personal altament especialitzat. En xarxes amb múltiples proveïdors, els processos d’integració entre els Sistemes de gestió de xarxa (NMS) i la resta de sistemes (per exemple, Sistemes de suport d’operacions - OSS i Sistemes de suport de negocis - BSS) són habitualment interminables i extremadament costosos a causa de la falta d’adopció d’interfícies estàndard per part dels diferents proveïdors de xarxa. A més, l’impacte creixent en les xarxes de transport dels nous fluxos de trànsit introduïts pel desplegament massius de Data Centers (DC), introdueix nous desafiaments que les arquitectures de gestió i control de les xarxes tradicionals que no estan llestes per afrontar. Per acabar de descriure el context, la cinquena generació de tecnologia mòbil (5G) també presenta nous requisits de xarxa altament exigents, com la necessitat de connectar a la xarxa milers de milions de dispositius nous, dins el context de l’Internet de les coses (IOT), o les noves aplicacions d’ultra baixa latència (com ara la cirurgia a distància) i les comunicacions vehiculars. Se suposa que tots aquests nous serveis, juntament amb l’accés millorat a la xarxa de banda ampla, es lliuraran a través de la mateixa infraestructura de xarxa. Aquesta tesi doctoral proposa una visió holística dels recursos de xarxa i cloud, basada en els principis introduïts per Software Defined Networking (SDN), com la solució per al disseny de una arquitectura de gestió extrem a extrem per a escenaris de xarxa multi-capa, multi-domini i consistents en múltiples tecnologies de transport. Aquesta arquitectura de gestió i control de xarxes transport i recursos IT, ha de ser capaç d’oferir serveis d’extrem a extrem, des de les xarxes intra-DC fins a les xarxes d’accés dels clients i oferir a més virtualització dels recursos de la xarxa, obrint la porta a noves formes de segmentació a les xarxes de transport i la infrastructura de cloud, pels propers desplegaments de 5G. La primera contribució d’aquesta tesi doctoral consisteix en la validació de diferents arquitectures d’orquestració de xarxa basades en SDN capaces de millorar les solucions existents per a la gestió i control de xarxes de transport troncals multi-domini i multicapa. Aquests problemes (gestió de xarxes multicapa i multi-domini), han estat avaluats de manera incremental, mitjançant el disseny i l’avaluació experimental, en entorns de proves reals, de diferents arquitectures de control i gestió. Un dels principals troballes d’aquest treball ha estat la necessitat de dissenyar un model d’informació comú per a les interfícies de gestió de xarxes, capaç de descriure els recursos i serveis de la xarxes transport multicapa. En aquesta línia, el Protocol de Control Orchestration (COP, en les seves sigles en anglès) ha estat proposat en aquesta Tesi, com una primera contribució cap a una interfície de gestió de xarxa estàndard basada en els principis bàsics de SDN. A més, en aquesta tesi presentem una arquitectura innovadora capaç de coordinar la gestió de els recursos IT juntament amb les xarxes inter i intra-DC. L’aprovisionament i la migració de màquines virtuals juntament amb la reconfiguració dinàmica de la xarxa, ha estat demostrat amb èxit en una escala de temps factible. A més, l’arquitectura incorpora una plataforma per a l’execució d’algorismes d’optimització de recursos, capaços de resoldre diferents problemes d’assignació, com el desplegament òptim de Grafs de Màquines Virtuals (VMG) en diferents ubicacions de DC que minimitzen la assignació de recursos de xarxa entre DC. També es presenta una solució bàsica per a aquest problema, així com els resultats de probabilitat de bloqueig per a diferents càrregues de xarxa. La tercera contribució principal és el resultat dels dos anteriors. Amb una infraestructura de xarxa i cloud convergent, controlada i operada de manera conjunta, la visió holística de la xarxa permet l’aprovisionament sota demanda de "network slices" que consisteixen en subconjunts de recursos d’xarxa i cloud, dedicats per a diferents clients, sobre una infraestructura de Data Centers distribuïda i interconnectada per una xarxa de transport òptica. Els últims capítols d’aquesta tesi tracten sobre la gestió i organització de "network slices" per a xarxes 5G en funció dels components de control i administració dissenyats i desenvolupats en els capítols anteriors. El disseny d’una de les primeres arquitectures de "network slicing" i el desplegament d’un "slice" de xarxa 5G totalment operatiu en un Testbed real, és una de les principals contribucions d’aquesta tesi.

Le découpage du réseau est une technologie clé des réseaux 5G, grâce à laquelle les opérateurs de réseaux mobiles peuvent créer des tranches de réseau indépendantes. Chaque tranche permet à des fournisseurs d'offrir des services personnalisés. Comme les tranches sont opérées sur une infrastructure de réseau commune gérée par un fournisseur d'infrastructure, il est essentiel de développer des méthodes de partage efficace des ressources. Cette thèse adopte le point de vue du fournisseur d'infrastructure et propose plusieurs méthodes de réservation de ressources pour les tranches de réseau. Actuellement, les chaines de fonctions appartenant à une tranche sont déployées séquentiellement sur l'infrastructure, sans avoir de garantie quant à la disponibilité des ressources. Afin d'aller au-delà de cette approche, nous considérons dans cette thèse des approches de réservation des ressources pour les tranches en considérant les besoins agrégés des chaines de fonctions avant le déploiement effectif des chaines de fonctions. Lorsque la réservation a abouti, les chaines de fonctions ont l'assurance de disposer de suffisamment de ressources lors de leur déploiement et de leur mise en service afin de satisfaire les exigences de qualité de service de la tranche. La réservation de ressources permet également d'accélérer la phase d'allocation de ressources des chaines de fonctions
Network 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

Avec les réseaux de cinquième génération (5G), plusieurs services hétérogènes sont supportés: le service enhanced Mobile BroadBand (eMBB) caractérisé par ses débits élevés, le service Ultra-Reliable Low-Latency Communications (URLLC) nécessitant une faible latence et le service massive Machine-Type Communications (mMTC) privilégiant une importante densité de connexions.Grâce au slicing, la coexistence de ces services sur le même réseau est possible. Le slicing divise le réseau en sous-réseaux logiques et isolés dont chaque partie est dénommée slice et attribuée à une catégorie de services.De plus, le Radio Access Network (RAN) est le lieu d'une transformation visant à désintégrer ses composants grâce à des organismes de normalisation comme l'alliance Open-RAN (O-RAN). Cette évolution apporte plusieurs avantages pour les opérateurs comme l'introduction de l'intelligence artificielle au niveau des contrôleurs.Dans ce contexte de slicing et d'évolution du RAN, l'optimisation des ressources radio est un défi majeur pour un opérateur mobile afin d'assurer la qualité de service des différents slices à partir d'algorithmes efficaces. Par conséquent, dans cette thèse, l'objectif est de proposer plusieurs algorithmes d'allocation de ressources radio en identifiant les indicateurs de performance nécessaires pour la prise de décisions. De plus, les différentes approches proposées sont comparées entre elles et à celles de l'état de l'art, y compris l'approche standard. Aussi, pour la plupart des solutions proposées, leur emplacement dans l'architecture O-RAN est discuté.Notre premier algorithme est basé sur le Dynamic Weighted Fair Queuing (DWFQ) dans un contexte multi-slice et multi-Virtual Operator (VO). Le but est de déterminer la portion de ressources attribuée à chaque VO dans chaque slice en utilisant la théorie des jeux.Dans la suite, on s'intéresse à la gestion des ressources radio au niveau d'un même opérateur. Pour cela, une deuxième approche se focalise sur l'allocation des ressources radio entre deux slices hétérogènes: eMBB et URLLC. Deux approches, centralisée basée sur le Deep-Q Networks (DQN) et distribuée basée sur un jeu non-coopératif, traitent ce problème où l'allocation des ressources se fait grâce à l'ingénierie de trafic.Dans la troisième contribution, on ajoute l'aspect numérologie (espacement entre sous-porteuses) au problème précédent avec l'étude de trois slices: eMBB, URLLC et mMTC. Pour cela, on divise la bande de l'opérateur en plusieurs Bandwidth Parts (BWPs) dont chacune est associée à une numérologie ce qui provoque l'Inter-Numerology Interference (INI). Par suite, on propose un algorithme à trois étages dont le premier étage utilise la théorie des jeux pour choisir la BWP qui servira les utilisateurs URLLC. Le deuxième étage utilise une heuristique pour déterminer la portion de ressources radio dédiée à chaque BWP. Le troisième étage utilise le DQN pour dimensionner une bande de garde entre les BWPs utilisant des numérologies différentes afin de réduire l'INI.Pour la suite, on garde toujours l'aspect multi-numérologies dans le problème mais on s'intéresse plutôt aux utilisateurs connectés simultanément à plusieurs slices. Pour ces utilisateurs, une latence additionnelle est générée à cause du BWP switching qui est nécessaire pour récupérer les ressources de chaque slice. Pour cela, notre quatrième contribution propose trois mécanismes innovants de BWP switching qui permettent de réduire la latence globale due à cet effet.Pour la dernière contribution, l'efficacité énergétique de ces utilisateurs est étudiée en proposant un algorithme qui sélectionne entre la configuration "single numerology" (une seule BWP pour tous les slices) et "multi-numerology" (BWP différente pour chaque slice) en se basant sur plusieurs facteurs comme le niveau de batterie. Cette sélection se fait à travers deux approches, centralisée basée sur un problème d'optimisation et distribuée basée sur la théorie des jeux
With Fifth Generation (5G) Networks, multiple heterogeneous services are supported such as the enhanced Mobile BroadBand (eMBB) service characterized by high throughput demand, the Ultra-Reliable Low-Latency Communications (URLLC) service requiring a low latency and the massive Machine-Type Communications (mMTC) service favoring a high density of connected devices.Thanks to slicing, these services can coexist on the same infrastructure. Slicing divides the network into multiple isolated logical networks named slices where each slice is attributed to a category of services.Furthermore, standardization bodies such as the Open-RAN alliance (O-RAN) focus on the evolution of the Radio Access Network (RAN) architecture including RAN components disaggregation. This evolution brings in many advantages for the operator such as the introduction of artificial intelligence at the level of the controllers.In this context of RAN evolution and slicing, the radio resource optimization is an important challenge for the mobile network operator to ensure Quality of Service (QoS) satisfaction for the different slices through efficient algorithms. Therefore, in this thesis, the objective is to propose various radio resource allocation algorithms based on the identification of the necessary Key Performance Indicators (KPIs) to take the appropriate decisions. Additionally, the proposed approaches are compared against each other and against other approaches from the state-of-the-art. Also, solutions implementation in an O-RAN compliant architecture is discussed.Our first algorithm is based on Dynamic Weighted Fair Queuing (DWFQ) in a multi-slice and multi-Virtual Operator (VO) context. The aim of this algorithm is to determine the resource portion that will be attributed to each VO in each slice using game theory.Next, we focus on the radio resource management at the level of a single operator. Therefore, the second contribution focuses on the radio resource allocation between two heterogeneous slices: eMBB and URLLC. Two approaches solve this problem where the radio resource allocation is based on traffic engineering. The first approach is a centralized one based on Deep-Q Networks (DQN) and the second is a distributed one based on a non-cooperative game.In our third contribution, we add the numerology (subcarrier spacing) aspect to the previous problem, while considering three slices: eMBB, URLLC and mMTC. For this reason, we divide the total band into multiple Bandwidth Parts (BWPs) each linked to a numerology. This causes a new type of interference called Inter-Numerology Interference (INI). Therefore, we propose a three-level algorithm where the first level uses game theory to choose the BWP that will serve the URLLC users. The second level uses heuristics to determine the portion of radio resources attributed to each BWP. The third level uses DQN to dimension the guard bands between the BWPs using different numerologies to reduce the INI effect.Subsequently, the multi-numerology aspect is retained in the problem, while considering multiple slices per user. For these users, an additional latency is induced due to BWP switching. The latter is necessary in order to retrieve the data of each slice. For this reason, our fourth contribution proposes three innovative BWP switching schemes that help to reduce the overall latency.As for our final contribution, we focus on the energy efficiency aspect of such users by proposing an algorithm that selects the most suitable BWP configuration: single numerology (a single BWP for all slices) or multi-numerology (different BWP for each slice) while taking into account multiple factors such as the battery level. This selection is done thanks to two approaches: a centralized one based on an optimization problem and a distributed one based on game theory

Cette thèse examine comment optimiser le placement de tranches (slices) de réseau dans les infrastructures distribuées à grande échelle en se concentrant sur des approches heuristiques en ligne et basées sur l'apprentissage par renforcement profond (DRL). Tout d'abord, nous nous appuyons sur la programmation linéaire en nombre entiers (ILP) pour proposer un modèle de données permettant le placement de tranches de réseau sur le bord et le cœur du réseau. Contrairement à la plupart des études relatives au placement de fonctions réseau virtualisées, le modèle ILP proposé prend en compte les topologies complexes des tranches de réseau et accorde une attention particulière à l'emplacement géographique des utilisateurs des tranches réseau et à son impact sur le calcul de la latence de bout en bout. Des expérimentations numériques nous ont permis de montrer la pertinence de la prise en compte des contraintes de localisation des utilisateurs.Ensuite, nous nous appuyons sur une approche appelée "Power of Two Choices" pour proposer un algorithme heuristique en ligne qui est adapté à supporter le placement sur des infrastructures distribuées à grande échelle tout en intégrant des contraintes spécifiques au bord du réseau. Les résultats de l'évaluation montrent la bonne performance de l'heuristique qui résout le problème en quelques secondes dans un scénario à grande échelle. L'heuristique améliore également le taux d'acceptation des demandes de placement de tranches de réseau par rapport à une solution déterministe en ligne en utilisant l'ILP.Enfin, nous étudions l'utilisation de méthodes de ML, et plus particulièrement de DRL, pour améliorer l'extensibilité et l'automatisation du placement de tranches réseau en considérant une version multi-objectif du problème. Nous proposons d'abord un algorithme DRL pour le placement de tranches réseau qui s'appuie sur l'algorithme "Advantage Actor Critic" pour un apprentissage rapide, et sur les réseaux convolutionels de graphes pour l'extraction de propriétés. Ensuite, nous proposons une approche que nous appelons "Heuristically Assisted DRL" (HA-DRL), qui utilise des heuristiques pour contrôler l'apprentissage et l'exécution de l'agent DRL. Nous évaluons cette solution par des simulations dans des conditions de charge de réseau stationnaire, ensuite cyclique et enfin non-stationnaire. Les résultats de l'évaluation montrent que le contrôle par heuristique est un moyen efficace d'accélérer le processus d'apprentissage du DRL, et permet d'obtenir un gain substantiel dans l'utilisation des ressources, de réduire la dégradation des performances et d'être plus fiable en cas de changements imprévisibles de la charge du réseau que les algorithmes DRL non contrôlés
This 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

In this work the 5G core network architecture has been explored: starting from the enabling technologies that are supporting the "revolution" and looking in depth at the current 4G LTE network architecture, we tried to find a solution to bridge the gap between these two totally different architecture. Once the solution has been found, we used a simulation platform provided by the ONF (Open Networking Foundation) that demonstrates the feasibility of such approach.

Future networks will pave the way for a myriad of applications with different requirements. In such a context, the today’s one-size-fits-all approach will not be able to efficiently address the different demands that verticals impose in terms of QoS and involved data volumes. To this end, network slicing is a new network paradigm which may provide the needed flexibility. It allows to offer multiple logical networks over a common infrastructure, tailored to the services which run on the network. In today’s Wi-Fi networks, all the users are connected to the same wireless channel, which allows service differentiation only at the traffic level. Thus, in this study, we propose a standard-compliant network slicing approach for the radio access segment of Wi-Fi, often neglected by the literature on network slicing. We present two algorithms to realize network slicing at the access level. The first assigns resources according to the requirements of the slices in a static way. On the other hand, the second, more advanced, dynamically configures the slices according to the network conditions and relevant KPIs. These techniques can be applied to the IEEE 802.11 standard and, in general, to all the protocols that use Carrier Sensing Multiple Access (CSMA) as channel access technique. The proposed algorithms were validated through extensive simulations, conducted with ns-3 network simulator and accompanied by theoretical calculations. Particular attention, often neglected in similar simulation-based works, has been paid to the electromagnetic properties of the spectrum, which play a fundamental role in radio communications. From the conducted simulations, we found that our slicing approaches largely outperform the today’s Wi-Fi access technique. They allow to reach higher goodput (i.e. a lower error probability) and lower latency, when needed. At the same time, tailored slicing saves energy to low-power devices and increases the spectrum efficiency.

5G is an enabler to several new use cases. To support all of them, the network infrastructure must be flexible and it should adapt to the different situations. This feature is powered by SDN, NFV, and Automation, three of the main pillars on which the 5G network is built.Traditional network management approaches may not be suitable for the 5G Core Network User Plane, which holds strict requirements in terms of latency and throughput. Therefore, Artificial Intelligence agents have been proposed to manage the 5G in a more efficient manner, delivering a more optimized allocation of the resources. This approach requires real-time monitoring of the data passing by the Core Network, a feature not standardized by the current protocols. In this thesis, the design of a monitoring protocol for the 5G Core Network User Plane has been studied, focusing on precise measurement of latencies. Then, a In-band Network Telemetry (INT) framework has been implemented on top of a User Plane Function prototype. The prototype is built on top of a novel User Plane implementation, based on chaining of atomic functions called micro-UPFs (µUPFs).While the main focus of this work has been latency measurement, packet counters, byte counters and Inter Packet Gap values can be collected from the framework, proving the main KPIs of a 5G User Plane. The INT framework has been implemented through two new µUPFs, one for updating the INT metadata and one for collecting them. These metadata are attached to the user packets as GTP-U extended header, maintaining compatibility with the standard protocol. Moreover, the implemented framework allows high flexibility through dynamic tuning of the parameters, providing mechanisms to reduce the amount of telemetry data generated and, thus, the system overhead.The framework has been tested on a physical setup of four server machines, abstracting a Core Network User Plane, connected with 10 Gbps NICs. In all the tests performed, the performances of the User Plane are affected by the new functionalities only when INT metadata are inserted very frequently. The results show that is possible to monitor the three main KPIs of a 5G User Plane without heavily limiting the system performances.
5G är en möjliggörare för flera nya användningsfall: för att stödja dem alla måste nätverksinfrastrukturen vara flexibel och den ska anpassa sig till de olika situationerna. Denna funktion drivs av SDN, NFV och Automation, tre av de viktigaste pelarna som 5G-nätverket är byggt på.Traditionella nätverkshanteringsstrategier kanske inte passar för 5G Core Network, som har strikta krav när det gäller latens och genomströmning. Därför har Artificial Intelligence-agenter föreslagits att hantera 5G på ett mer effektivt sätt, vilket ger en mer optimerad fördelning av resurserna. Detta tillvägagångssätt kräver realtidsövervakning av data som passerar via Core Network, en funktion som inte standardiseras med de aktuella protokollen.I denna avhandling har utformningen av ett övervakningsprotokoll för 5G Core Network User Plane studerats med fokus på exakt mätning av latenser. Sedan har ett in-band Network Telemetry (INT) -ramverk implementerats ovanpå en prototyp för User Plane Function. Denna prototyp utnyttjade Chain Controllerarkitekturen, en ny användarplan-implementering baserad på kedjan av atomfunktioner som kallas µUPF.Medan huvudfokuset för detta arbete har varit latensmätning, kan paketräknare, byttäknare och Inter Packet Gap-värden samlas in från ramverket, vilket bevisar de viktigaste KPI: erna i ett 5G-nätverk. INT-ramverket har implementerats genom två nya µUPF, en för att uppdatera INT-metadata och en för att samla dem. Dessa metadata är anslutna till användarpaketen som GTP-U utökad rubrik, bibehållande kompatibilitet med standardprotokollet. Dessutom tillåter det implementerade ramverket hög flexibilitet som tillåter dynamisk inställning av parametrarna, tillhandahåller mekanismer för att minska mängden telemetri-data som genereras och därmed systemomkostnaderna.Ramverket har testats på en fysisk installation av fyra servermaskiner som abstraherar ett Core Network User Plane, anslutet med 10 Gbps NIC. I samtliga tester påverkas testbäddens prestationer av de nya funktionerna först när INT-metadata sätts in mycket ofta. Resultaten visar att det är möjligt att övervaka de tre huvudsakliga KPI: erna i ett 5G-nätverk utan att starkt begränsa systemprestanda.

With advancements in the mobile network architecture, from the Fourth Generation to the Fifth Generation, a vast number of new use cases becomes available. Many use cases require cloud-based services, where a service is deployed close to the user. For a user to communicate with a service, it connects to the mobile network base station, Fifth Generation Core network and then to the service. When the user changes physical location, the mobile network and the service must apply mobility techniques. This is to prevent tromboned traffic and provide low latency between user and service. When a handover occurs, so that a user’s attachment point to the mobile network is changed from the one base station to another and the User Plane Function changes, the cloud-based service may have to seamlessly move from one cloud to another as well. In this thesis, a Service mobility framework is proposed and implemented, which enables service live migration between edge clouds and it provides simple RESTful APIs. The evaluation of the framework shows that the proposed implementation adds low delays to the total migration time and the service downtime is also shown to be low in the case of video streaming with no service interruption.
Med framsteg i det mobila nätverkets arkitektur, sett från den Fjärde Generationen till den Femte Generationen, så blir nya användningsområden tillgängliga. Bland de nya användningsområdena inkluderas molnbaserade tjänster, där tjänster är placerade nära användare, dessutom har vissa områden behov av dessa molnbaserade tjänster. För att en användare ska kunna kommunicera med en tjänst så måste den först ansluta till det mobila nätverkets basstationer och sedan till Femte Generationens kärnnätverk, för att sedan kunna kommunicera med tjänsten. När användaren förflyttar sig från en plats till en annan, så måste det mobila nätverket och tjänsten tillämpa rörlighetstekniker, som förflyttning av tjänsten. Förflyttningen är för att förhindra trombonerad trafik och att förse låg latens mellan användare och tjänst. När en överlämning sker, d.v.s att en användares kopplingspunkt till det mobila nätverket ändras, från en basstation till en annan, och att User Plane Function ändras, så kan även den molnbaserade tjänsten förflytta sig sömlöst från ett moln till ett annat. I denna avhandling presenteras ett tjänströrlighetsramverk som möjliggör tjänströrlighet mellan moln och erbjuder enkla RESTfulla API:er. Evaluering av ramverket visar att implementationen bidrar med låga fördröjningar till den totala migrations tiden samt att tjänster med videoströmming har lågt driftstopp utan tjänstavbrott.

Abstract. The global communication network is going through major transformation from conventional to more versatile and diversified network approaches. With the advent of virtualization and cloud technology, information technology (IT) is merging with telecommunications to alter the conventional approaches of traditional proprietary networking techniques. From radio to network and applications, the existing infrastructure lacks several features that we wished to be part of 5th Generation Mobile Networks (5G). Having a support for large number of applications, Internet of Things (IoT) will bring a major evolution by creating a comfortable, flexible and an automated environment for end users. A network having the capability to support radio protocols on top of basic networking protocols, when blended with a platform which can generate IoT use cases, can make the expectations of 5G a reality. Low Power Wide Area Network (LPWAN) technologies can be utilized with other emerging and suitable technologies for IoT applications. To implement a network where all the technologies can be deployed virtually to serve their applications within a single cloud, Network Functions Virtualization (NFV) and Software Defined Network (SDN) is introduced to implement such a networking possibility for upcoming technologies. The 5G Test Network (5GTN), a testbed for implementing and testing 5G features in real time, is deployed in virtual platform which allows to add other technologies for IoT applications. To implement a network with an IoT enabler technology, LoRa Wide Area Network (LoRaWAN) technology can be integrated to test the feasibility and capability of IoT implications. LoRaWAN being an IoT enabler technology is chosen out of several possibilities to be integrated with the 5GTN. Using MultiConnect Conduit as a gateway, the integration is realized by establishing point to point protocol (PPP) connection with eNodeB. Once the connection is established, LoRa packets are forwarded to the ThingWorx IoT cloud and responses can be received by the end-devices from that IoT cloud by using Message Queuing Telemetry Transport (MQTT) protocol. Wireshark, an open source packet analyser, is then used to ensure successful transmission of packets to the ThingWorx using the 5GTN default packet routes.

La codificación de red (NC) ha surgido recientemente como una nueva solución para mejorar el rendimiento de la red en términos de rendimiento y fiabilidad. Sin embargo, la naturaleza multiusuario de NC y su aplicabilidad inherente a la ingeniería de flujo versátil en todas las capas de la pila de protocolos requieren nuevos enfoques de diseño de sistemas inalámbricos. El objetivo de esta tesis es estudiar el diseño de NC como una funcionalidad de red ofrecida a los diseñadores de servicios de comunicación inalámbrica 5G. El diseño facilitaría el control del rendimiento de la red, la confiabilidad y la conectividad a través de redes inalámbricas 5G. Las contribuciones de esta tesis son las siguientes. Primero desarrollamos un diseño de Funcionalidad de codificación de red como una caja de herramientas de dominios de diseño NC y mostramos cómo se puede integrar en las infraestructuras virtualizadas actuales. En segundo lugar, evaluamos el rendimiento de longitud finita de diferentes códigos de red usando matrices aleatorias vs Pascal. Modelamos el proceso de codificación, recodificación y decodificación de diferentes esquemas de codificación en notación de matriz y las correspondientes probabilidades de error. A continuación, proponemos un algoritmo de búsqueda binaria para identificar la velocidad de codificación óptima para algunas tasas de pérdida de paquetes de destino específicas dada una longitud de bloque de codificación predefinida. Nos enfocaremos en los códigos de logro de capacidad y los esquemas de codificación con la programación de escenarios representativos y mostraremos la compensación de la tasa de retardo alcanzable entre los códigos aleatorios y los códigos estructurados con la programación. En la última parte de esta tesis, validamos el diseño de NCF propuesto para un caso de uso completo para mejorar la conectividad de los dispositivos de red móvil ad-hoc (MANET) sobre las redes convergidas de nubes satelitales en aplicaciones de emergencia. La idea clave es que en un escenario de emergencia puede no haber acceso directo a la niebla o la computación en la nube, que luego se proporcionará por satélite y los únicos recursos computacionales locales disponibles son los dispositivos MANET. Para resolver esta situación, definimos un NCF a nivel de paquetes con entradas de objetivos de calidad del servicio de datos, restricciones de computación local y estadísticas por ruta. Las salidas son tasas de codificación centralmente optimizadas que equilibran los recursos computacionales por nodo y la cobertura resultante.
Network coding (NC) has recently emerged as a new solution for improving network performance in terms of throughput and reliability. However, the multi-user nature of NC and its inherent applicability to versatile flow engineering across all layers of the protocol stack, call for novel wireless system design approaches. The goal of this thesis is to study the design of NC as a network functionality offered to the 5G wireless communication service designers. The design would facilitate the control of network throughput, reliability, and connectivity over 5G wireless networks. The contributions of this thesis are the following. We first develop a design of Network Coding Functionality as a toolbox of NC design domains and show how it can be integrated in current virtualized infrastructures. Second, we evaluate the finite-length performance of different network codes using random vs Pascal matrices. We model the encoding, re-encoding, and decoding process of different coding schemes in matrix notation and corresponding error probabilities. We then propose a binary searching algorithm to identify optimal coding rate for some specific target packet loss rates given a pre-defined coding block-length. We will focus on capacity-achieving codes and coding schemes with scheduling for representative scenarios and show the achievable rate-delay trade-off between random codes and structured codes with scheduling. In the last part of this thesis, we validate the proposed NCF design for a complete use case to enhance connectivity of Mobile Ad-hoc Network (MANET) devices over converged satellite-cloud networks in emergency applications. The key insight is that in an emergency scenario there may not be direct access to fog or cloud computing, which will then be provided via satellite and the only local computational resources available are the MANET devices. To solve this situation, we define a packet-level NCF with inputs from data service quality targets, local computation constraints and per-path statistics. Outputs are centrally-optimized coding rates balancing per-node computational resources and resulting coverage.

This Ph.D. thesis investigates the resilient and cost-efficient design of both C-RAN and Xhaul architectures. Minimization of network resources as well as reuse of already deployed infrastructure, either based on fiber, wavelength, bandwidth or Processing Units (PU), is investigated and shown to be effective to reduce the overall cost. Moreover, the design of a survivable network against a single node (Baseband Unit hotel (BBU), Centralized/Distributed Unit (CU/DU) or link failure proposed. The novel function location algorithm, which adopts dynamic function chaining in relation to the evolution of the traffic estimation also proposed and showed remarkable improvement in terms of bandwidth saving and multiplexing gain with respect to conventional C-RAN. Finally, the adoption of Ethernet-based fronthaul and the introduction of hybrid switches is pursued to further decrease network cost by increasing optical resource usage.

Communication network reliability analysis is of great significance in the practice of network construction management and operation of telecom operators. It can provide an important scientific basis for the formulation of network construction strategy and the optimization and adjustment of network performance. Combining the theoretical results of reliability analysis with engineering application practice effectively in communication network operation has always been a research difficulty in communication network operation, which has high theoretical research value and market application prospect. This thesis work focuses on the improved network optimization method, discusses and extends the key technologies such as network topology, network model analysis index, network topology analysis method, calculation and analysis of evaluation results. Based on the classical network reliability analysis method, this thesis also does the following work, defines several main parameters that affect the network reliability analysis, puts forward the R-T (Ring-Tree) analysis method and the concept of branch line depth, and then finds out the approximate relationship between the branch line depth and network reliability through mathematical derivation. Finally, based on the theory proposed in this paper, a set of targeted network analysis tools is developed, and the proposed method is verified by using the local IP Bearer Network engineering data. The simulation results show that this method can quickly analyze the network reliability, significantly reduce the workload of data analysis, and give the targeted network optimization scheme. It can help the network operators to improve the network reliability quickly and effectively improve the network operation, management and maintenance ability of the operators.

This dissertation is directed towards improving the performance of 5G Wireless Fronthaul Networks and Wireless Sensor Networks, as measured by reliability, fault recovery time, energy consumption, efficiency, and security of transmissions, beyond what is achievable with conventional error control technology. To achieve these ambitious goals, the research is focused on novel applications of networking techniques, such as Diversity Coding, where a feedforward network design uses forward error control across spatially diverse paths to enable reliable wireless networking with minimal delay, in a wide variety of application scenarios. These applications include Cloud-Radio Access Networks (C-RANs), which is an emerging 5G wireless network architecture, where Remote Radio Heads (RRHs) are connected to the centralized Baseband Unit (BBU) via fronthaul networks, to enable near-instantaneous recovery from link/node failures. In addition, the ability of Diversity Coding to recover from multiple simultaneous link failures is demonstrated in many network scenarios. Furthermore, the ability of Diversity Coding to enable significantly simpler and thus lower-cost routing than other types of restoration techniques is demonstrated. Achieving high throughput for broadcasting/multicasting applications, with the required level of reliability is critical for the efficient operation of 5G wireless infrastructure networks. To improve the performance of C-RAN networks, a novel technology, Diversity and Network Coding (DC-NC), which synergistically combines Diversity Coding and Network Coding, is introduced. Application of DC-NC to several 5G fronthaul networks, enables these networks to provide high throughput and near-instant recovery in the presence of link and node failures. Also, the application of DC-NC coding to enhance the performance of downlink Joint Transmission-Coordinated Multi Point (JT-CoMP) in 5G wireless fronthaul C-RANs is demonstrated. In all these scenarios, it is shown that DC-NC coding can provide efficient transmission and reduce the resource consumption in the network by about one-third for broadcasting/multicasting applications, while simultaneously enabling near-instantaneous latency in recovery from multiple link/node failures in fronthaul networks. In addition, it is shown by applying the DC-NC coding, the number of redundant links that uses to provide the required level of reliability, which is an important metric to evaluate any protection system, is reduced by about 30%-40% when compared to that of Diversity Coding. With the additional goal of further reducing of the recovery time from multiple link/node failures and maximizing the network reliability, DC-NC coding is further improved to be able to tolerate multiple, simultaneous link failures with less computational complexity and lower energy consumption. This is accomplished by modifying Triangular Network Coding (TNC) and synergistically combining TNC with Diversity Coding to create enhanced DC-NC (eDC-NC), that is applied to Fog computing-based Radio Access Networks (F-RAN) and Wireless Sensor Networks (WSN). Furthermore, it is demonstrated that the redundancy percentage for protecting against n link failures is inversely related to the number of source data streams, which illustrates the scalability of eDC-NC coding. Solutions to enable synchronized broadcasting are proposed for different situations. The ability of eDC-NC coding scheme to provide efficient and secure broadcasting for 5G wireless F-RAN fronthaul networks is also demonstrated. The security of the broadcasting data streams can be obtained more efficiently than standardized methods such as Secure Multicasting using Secret (Shared) Key Cryptography.

Network slicing has recently been proposed as one of the main enablers for 5G networks; it is bound to cope with the increasing and heterogeneous performance requirements of these systems. To "slice'' a network is to partition a shared physical network into several self-contained logical pieces (slices) that can be tailored to offer different functional or performance requirements. Moreover, a key characteristic of the slicing paradigm is to provide resource isolation as well as an efficient use of resources. In this context, a slice is envisioned as an end-to-end virtual network which permits that the infrastructure operators lease their resources to service providers (tenants) through the dynamic, and on-demand, deployment of slices. Tenants may have complete control over the slice functions and resources, and employ them to satisfy their client’s demands. Recent works on slicing for Radio Access Networks (RANs) just focus on general architectures and frameworks for the management and instantiation of network slices avoiding details on how the slices are implemented and enforced in the wireless devices. Even more, while some techniques for slice enforcement already exist, most of them concentrate on cellular technologies, ignoring WiFi networks. Despite of their growing relevance and ubiquity, there are not many works addressing the challenges that appear when trying to apply slicing techniques over WiFi networks. In this scenario, this thesis contributes to the problem of slicing WiFi networks by proposing a solution to enforce and control slices in WiFi Access Points. The focus of this work is on a particular and complex variant of network slicing called QoS Slicing, in which slices have specific performance requirements. The main thesis contributions are divided in three: (1) a detailed analysis of the network slicing problem in RANs in general and in WiFi in particular, as well as a study and definition of the QoS Slicing problem, (2) a resource allocation model and mechanism for Wifi devices, and (3) a QoS Slicing solution to enforce and control slices with performance requirements in WiFi Access Points. Given the novelty of the slicing concept and the complexity of the problem, a detailed study of the slicing problem was performed providing a comprehensive definition of the slicing concept, as well as a classification of the slicing variants. It is also introduced the two main problems of slicing wireless resources: resource allocation and isolation. In the scope of those problems, this thesis contributes with a novel approach where the resource allocation problem is divided on two sub-tasks: Dynamic Resource Allocation, and Enforcement and Control. As a previous step to the construction of a QoS Slicing solution, it is proposed a novel method of proportionally distributing resources in WiFi networks, by means of the airtime. The proposed mechanism (called ATERR) is based on considering the airtime as the wireless resource to be shared and allocated. An analytical model of the ATERR algorithm is also developed, which shed light on how such resources could be split and on the capacities and limitations of the proposal. The validity of the proposed model is assessed by means of a simulation-based evaluation on the NS-3 framework. Finally, regarding the QoS Slicing problem, it is considered two different performance requirements: a guaranteed minimum bit rate and a maximum allowable delay. The resource allocation problem to the different slices is formulated as a stochastic optimization problem, where each slice's requirement of bit rate and delay is modeled as a constraint. A solution to the aforementioned problem is devised using the Lyapunov drift optimization theory to obtain an approximate deterministic problem. With this solution, it is developed a novel queuing and scheduling algorithm which allows implementing the obtained solution in WiFi devices.
Network slicing ha estat recentment proposat com un dels aspectes claus de les xarxes 5G i s'espera que permeti afrontar les creixents demandes de rendiment que tindran aquests sistemes. Fer slicing consisteix en fer particions d'una xarxa física compartida en diverses parts (slices) lògiques autocontenidas que poden ser adaptades per oferir diferents requeriments funcionals o de rendiment. Més encara, una característica clau del paradigma de slicing és el de proveir aïllament dels recursos així com permetre un ús eficient dels mateixos. En aquest context, una slice es pot considerar com una xarxa virtual d'extrem a extrem que permet als operadors d'infraestructura arrendar els seus recursos a proveïdors de servei (arrendatari) mitjançant el desplegament dinàmic i sota demanda de slices. Els arrendataris poden tenir control complet sobre els recursos i funcions de la slice i utilitzar-los per satisfer les demandes dels seus clients. Treballs recents sobre slicing en xarxes d'accés sense fil s'han enfocat en arquitectures generals i esquemes de gestió per al desplegament de slicing. En aquest sentit, no s'ha aprofundit en detalls de com s'implementen i controlen les slices en els dispositius sense fils. A més, encara hi ha algunes tècniques per al control de slices, la majoria es concentren en tecnologies per a xarxes mòbils i no tenen en compte les xarxes WiFi malgrat la seva creixent rellevància i omnipresència. En aquest escenari, aquesta tesi contribueix al problema de slicing en xarxes WiFi proposant una solució per implementar i controlar slices en punts d'accés WiFi. El treball es concentra en slicing amb qualitat de servei (QoS Slicing), una variant complexa del problema on les slices tenen requeriments de rendiment específics. Les principals contribucions de la tesi es divideixen en tres: (1) una detallada anàlisi del problema de network slicing en xarxes d'accés sense fil i en particular en WiFi, així com un estudi i definició dels problemes de QoS Slicing, (2) un model i mecanisme per a l'assignació de recursos en dispositius WiFi, i (3) una solució per QoS Slicing que implementa i controla slices amb requeriments de rendiment en punts d'accés WiFi. Donada la novetat del concepte de slicing i la complexitat del problema, es va realitzar un estudi detallat del problema de slicing on es proveeix una definició completa del concepte de slicing. A més, s'introdueixen els dos principals problemes del slicing: l'assignació de recursos i l'aïllament. En aquest sentit, aquesta tesi contribueix amb una estratègia original on el problema d'assignació de recursos es divideix en dues tasques: l'assignació dinàmica de recursos i el control de l'assignació. Com un pas previ a la construcció d'una solució per QoS Slicing, es proposa un mètode original per a la distribució proporcional de recursos en xarxes WiFi mitjançant el control del temps de transmissió. El mecanisme proposat (anomenat ATERR) es basa en considerar el temps de transmissió com el recurs a ser compartit i assignat. També es va desenvolupar un model analític de l'algoritme ATERR del qual es poden obtenir les capacitats i limitacions del mecanisme. La validesa del model proposat és estudiada mitjançant una avaluació basada en simulacions sobre l'entorn NS-3. Finalment, pel que fa al problema de QoS Slicing, es van considerar dos requeriments diferents: una garantia de taxa de transmissió mínima i un màxim de latència permès. El problema d'assignació de recursos per a les diferents slices es va formular com un problema d'optimització estocàstica on els requeriments de cada slice es modelen com una restricció. Es va elaborar una solució al problema anterior utilitzant la teoria d'optimització de Lyapunov per obtenir un problema determinista aproximat. Amb aquesta solució, es va desenvolupar un algoritme d'assignació del temps de transmissió per a dispositius WiFi.

The advent of 5th generation of mobile networks (5G) will introduce some new challenges for the transport network. Different strategies can be employed by the network providers to address these challenges with the aim to achieve an efficient utilization of network resources. The most feasible option to achieve this goal is to introduce intelligence in the transport infrastructure by designing a flexible and programmable transport network. Network function virtualization (NFV) and dynamic resource sharing (DRS) are two possible techniques for realizing a flexible transport network. NFV allows to dynamically push network functions to different locations in the network, while DRS allows for sharing transport resources in a flexible manner. Both of these strategies can be realized by employing a programmable control framework based on software defined networking (SDN), which has implications on both the network data and control planes. However, this thesis specifically focuses on the data plane aspects of NFV and the control plane aspects of DRS. Considering the network caching as a specific example of network function, the data plane aspects of NFV are studied in terms of different architectural options for cache placement in order to see which options are the most efficient in terms of network power consumption and cost. The results presented in this thesis show that placing large-sized caches farther in the network for a large group of users is the most efficient approach. The control plane aspects of DRS are analyzed in terms of which provisioning strategy should be used for sharing a limited amount of transport resources. The analysis is presented for both a single-tenant case (i.e., where the role of service and network provider is played by the same entity), and a multi-tenant case (i.e., where a network provider manages the resources assigned to different service providers in an intelligent way). The results show that DRS performs much better than the conventional static approach (i.e., without sharing of resources), which translates into significant cost savings for the network providers.

QC 20161115

La 5G apporte un nouveau concept, le network slicing (découpage du réseau en tranches). Cette technologie permet de généraliser le modèle économique des MVNO à des entreprises qui ont besoin d’opérer un réseau, sans que cela ne soit leur cœur de métier. Chaque tranche (slice) est un réseau virtuel de bout en bout, dédié et personnalisé, au-dessus d’une infrastructure partagée ; cette infrastructure elle-même être fournie par l’interconnexion de fournisseurs d’infrastructure: nous parlons dans ce cas d’infrastructure multi-domaine.L’objectif de cette thèse est d’étudier l’allocation de ces tranches dans une telle infrastructure multi-domaine. Le problème est connu comme l’incorporation de réseau virtuel (Virtual Network Embedding (VNE)). Il s’agit d’un problème NP-difficile. Pratiquement, le problème VNE recherche à quelles ressources physiques associer un ensemble d’éléments virtuels. Les ressources physiques décrivent ce qu’elles peuvent offrir. Les éléments virtuels décrivent ce qu’ils exigent. La mise en relation de ces offres et de ces demandes est la clé pour résoudre le problème VNE.En l’espèce, nous nous sommes intéressés à la modélisation et à la mise en place d’exigences de sécurité. En effet, nous nous attendons à ce que les acteurs à l’initiative des tranches appartiennent à des sphères éloignées des télécommunications. Or de la même façon qu’ils connaissent peu ce domaine, nous pouvons nous attendre à ce que leurs besoins, notamment de sécurité, s’expriment d’une façon sans précédent dans le contexte des tranches.Cette thèse présente un algorithme capable de traiter des exigences variées selon un modèle extensible fondé sur un solveur de satisfiabilité appliqué à des théories décidables (Satisfiability Modulo Theories (SMT)). Comparée à la programmation linéaire (Integer Linear Programming (ILP)), plus commune dans le domaine des VNE, cette formulation permet d’exprimer les contraintes à satisfaire de façon plus transparente, et d’auditer l’ensemble des contraintes.De plus, ayant conscience que les fournisseurs d’infrastructure sont réticents à exposer les informations relatives à leurs ressources physiques, nous proposons une résolution limitant cette exposition. Ce système a été implémenté et testé avec succès au cours du doctorat
5G brings a new concept called network slicing. This technology makes it possible to generalize the business model of MVNOs to companies in need to operate a network, without it being their core business. Each slice is an end-to-end, dedicated and customized virtual network, over a shared infrastructure; this infrastructure itself is provided by the interconnection of infrastructure providers: we refer to this case as a multi-domain infrastructure.The objective of this thesis is to study the allocation of these slices in such a multi-domain infrastructure. The problem is known as Virtual Network Embedding (VNE). It is an NP-hard problem. Practically, the VNE problem looks for which physical resources to associate a set of virtual elements. Physical resources describe what they can offer. Virtual elements describe what they require. Linking these offers and requests is the key to solve the VNE problem.In this thesis, we focused on modeling and implementing security requirements. Indeed, we expect that the initiators of the slices belong to areas distant from telecommunications. In the same way that they know little about this field, we can expect that their needs, especially in security, are novel in the slice context.This thesis presents an algorithm able to handling various requirements, according to an extensible model based on a Satisfiability Modulo Theories (SMT) solver. Compared to Integer Linear Programming (ILP), more common in the VNE field, this formulation allows to express the satisfaction constraints in a more transparent way, and allows to audit all the constraints.Moreover, being aware that infrastructure providers are reluctant to disclose information about their physical resources, we propose a resolution limiting this disclosure. This system has been successfully implemented and tested during the Ph.D

From the first generation, 1G, to the fourth generation, 4G, the development and technological advancements in telecommunications network systems have been remarkable. Faster and better connections have opened up for new markets, ideas and possibilities, to that extent that there now is a demand that surpasses the supply. Despite all these advancements made in the mobile communications field most of the concept of how the technology works and its infrastructure has remained the same. This however, is about to change with the introduction of the fifth generation (5G) mobile communication. With the introduction of 5G much of the technology introduced will be different from that of previous generations. This change extends to include the entire infrastructure of the mobile communications system. With these major changes, many of the tools available today for telecommunications network evaluation do not really suffice to include the 5G network standard. For this reason, there is a need to develop a new kind of tool that will be able to include the changes brought by this new network standard. In this thesis a simulation framework adapted for the next generation telecommunication standard 5G is set to be developed. This framework should include many of the characteristics that set 5G aside from previous generations.

With 5G technology, networks are expected to offer high speed with ultra-low latency among different users. Maintaining the current network architecture will lead to an unsustainable transport delay and jitters increase. Limiting the transport delay and the jitters have become a necessity for mobile network operators. The main requirement in 5G networks is the demand of limiting the transport delay. This, thesis proposes a novel mechanism to minimize packet delay and delay variation in 5G Ethernet fronthaul network. The goal is to achieve bounded delay aggregation of traffic ,suitable for application in fronthaul transport. Hybrid switching technology can be adopted to provide efficient fronthaul in 5G. Hybrid switches allows to multiplex traffics with different characteristics over the same wavelengths, thus increasing the network resource utilization. This thesis proposes a scheduling mechanism for hybrid switches to aggregate streams from the network, the Bypass traffic (BP), and the traffic from the fronthaul links, the ADD traffic, using an algorithm which looks for the time gaps in the BP stream for the insertion of the ADD traffic. The proposed strategy minimizes the delay of packets by making use of the available gaps during the transmission to limit the network latency. The size of the required time gaps, the time window, is suitably reduced by dividing the timeout time duration with number of intervals (N) with the Window reduction mechanism so that the delay variation or jitter of both aggregated streams are bounded. The results demonstrate that the aforementioned requirements are can be achieved by suitably tuning the parameters of the algorithm inputs, mainly the window reduction factor, timeout time duration and the number of intervals, resulting in values of packet delay and delay variation bounded at 10 microseconds or even lower up to 85-90percent carried load of aggregated flows. Hence, we show their suitability for delay sensitive future applications in 5G networking.

Network data rates are growing rapidly. The data rates provided to the customers by their network providers vary from Mbps to Gbps. However, rarely do users get the promised peak throughput. In cellular networks, network conditions change based on obstacles, weather conditions between the client and the base stations, and even the movement of objects and people. As a result of the changes in the radio link, the data transfer rate can change rapidly, hence devices needs to adjust their communications based on the currently available data rate. The Transmission Control Protocol (TCP) is widely used for reliable data transfer over networks. However, TCP was initially designed when link data rates were much lower than the link data rates commonly available today. As a result, TCP does not perform well at high data rates, despite some of the changes that have been made to the protocol to support high data rate links. Moreover, TCP has problems adapting to large changes in link bandwidth (not caused by congestion), resulting in a lower average throughput than the link could potentially deliver. This thesis evaluates two different versions of the TCP protocol (e.g., TCP Reno and Cubic TCP) and proposes a network coding scheme to enhance users’ experience when communicating over unstable radio links. The performance of the two TCP protocols and Random Linear Network Coding (RLNC) scheme were measured in an emulated network environment. The results of these measurements were analyzed and evaluated. The analysis shows that RLNC can provide a higher throughput than TCP over a network with high packet loss. However, RLNC is a UDP based solution and does not implement congestion control algorithms or reliability. A new solution is proposed that increases reliability and implements network adaptation in RLNC solutions. The results obtained in this thesis can be used to develop a new protocol to increases the quality of users’ experience in high loss networks.
Datahastigheter över nätverk ökar drastiskt. Datahastigheterna som ges tillgängliga till användare av deras respektive dataleverantör kan variera från Mbit/s till Gbit/s. Det är dock inte ofta användare får ut vad som har lovats. I mobila nätverk kan nätverkets tillstånd ändras baserat på hinder, väderleksförhållanden mellan en klient och basstationerna, till och med beroende på förflyttning av objekt eller människor. På grund av detta så behöver användares utrustning anpassa dess kommunikation, baserat på den för närvarande tillgängliga datahastigheten. Transmission Control Protocol (TCP) används i stor utsträckning vid behovet av tillförlitlig dataöverföring över nätverk. Däremot så designades TCP när länkdatahastigheterna var mycket lägre än vad som är vanligen tillgängligt idag. På grund av detta så presterar inte TCP över höga datahastigheter, trots ändringar som har gjorts i protokollet för att stödja höghastighets datalänkar. Utöver det så har TCP svårt att anpassa sig efter stora ändringar i länkens bandbredd (som inte är orsakat av stockning), som resulterar i en mindre genomsnitts-dataström än vad länken potentiellt hade kunnat ge. Detta examensarbete utvärderar två olika versioner av TCP (e.g., TCP Reno och Cubic TCP) och föreslår ett sätt att använda network coding för att öka användares upplevelse vid dataöverföring över instabila radio länkar. Prestationerna av de två TCP versionerna och Random Linear Network Coding (RLNC) metoden har blivit mätt i en emulerad nätverksmiljö. Resultaten från dessa mätningar blev analyserade och utvärderade. Analysen visar att RLNC kan ge en högre dataström än TCP över ett nätverk med hög risk för paketförluster. Däremot så är RLNC en User Datagram Protocol (UDP) baserad lösning, och därav inte implementerar trängselkontrolls-algoritmer eller tillförlitlighet. Ett förslag till en ny lösning som ökar tillförlitlighet och implementerar nätverksanpassning till RLNC lösningar har presenterats. Resultaten från detta examensarbete kan användas till att utveckla nya protokoll för att öka kvalitén av användares upplevelse i nätverk med risk för hög paketförlust.

Avec la croissance rapide de la demande de trafic de données des clients, l'amélioration de la capacité du système et l'augmentation du débit des utilisateurs sont devenues des préoccupations essentielles pour le futur réseau de communication sans fil de cinquième génération. Dans ce contexte, la communication terminal-à-terminal (Device-to-Device D2D) et le Full Duplex (FD) sont proposés comme solutions potentielles pour augmenter l’efficacité spectrale et le débit des utilisateurs dans un réseau cellulaire. Le D2D permet à deux périphériques proches de communiquer sans participation de la station de base ou avec une participation limitée. D'autre part, la communication en FD permet une transmission et une réception simultanées dans la même bande de fréquence. En raison de la propriété de distance courte des liaisons D2D, exploiter la technologie FD dans la communication D2D est un excellent choix pour améliorer encore plus l’efficacité spectrale cellulaire et le débit des utilisateurs. Cependant, les émetteurs-récepteurs FD constituent de nouveau défis pour la communication D2D. Par exemple, en FD les émetteurs-récepteurs ne peuvent pas supprimer d’une manière parfaite l’auto-interférence (SI) générée au niveau des récepteurs lors de la transmission des données (par le propre émetteur du dispositif cellulaire). Ainsi, l’auto-interférence résiduelle qui est étroitement liée à la valeur de la puissance de l’émetteur affecte fortement les performances de la transmission FD. De plus, la technique en FD crée des interférences supplémentaires dans le réseau, ce qui peut dégrader ses performances par rapport à la transmission en semi-duplex (Half-duplex HD). Ainsi, une bonne gestion des ressources radio est nécessaire pour exploiter les avantages de la FD et garantir la qualité de service (QoS) des utilisateurs. Les travaux de cette thèse portent sur l'allocation de puissance et l'attribution de canaux d'un réseau FD-D2D. En particulier, cette thèse aborde d’abord le problème de l’allocation de puissance et propose une méthode d'allocation de puissance (PA) optimale centralisée simple mais efficace, puis développe le schéma optimal conjoint d’AP et d’AC pour un réseau FD-D2D. Un algorithme de complexité réduite CATPA, basé sur une allocation CA suivie d'une allocation PA, est aussi développée et proposé. La thèse présente à la fin une stratégie efficace d'AP décentralisée en utilisant les outils de la théorie des jeux
With the rapidly growing of the customers' data traffic demand, improving the system capacity and increasing the user throughput have become essential concerns for the future 5G wireless communication network. In this context, D2D communication and FD are proposed as potential solutions to increase the spatial spectrum utilization and the user rate in a cellular network. D2D allows two nearby devices to communicate without BS participation or with limited participation. On the other hand, FD communication enables simultaneous transmission and reception in the same frequency band. Due to the short distance property of D2D links, exploiting the FD technology in D2D communication is an excellent choice to further improve the cellular spectrum efficiency and the users’ throughput. However, practical FD transceivers add new challenges for D2D communication. For instance, the existing FD devices cannot perfectly eliminate the SI imposed on the receiver by the node’s own transmitter. Thus, the RSI which is tightly related to the transmitter power value highly affects the performance of FD transmission. Moreover, the FD technique creates additional interference in the network which may degrade its performance when compared with the half-duplex transmission. Thus, proper radio resource management is needed to exploit the benefits of FD and guarantee the QoS of the users. The works in this dissertation focus on the PA and CA of a FD-D2D network. In particular, this thesis first addresses the PA problem and proposes a simple yet efficient centralized optimal PA framework, and next, it derives the optimal joint PA and CA scheme for an FD-D2D network. A simple sub-optimal algorithm for resource allocation named CATPA, based on CA followed by PA, is also derived and proposed. This dissertation also develops, in the end, an efficient decentralized PA using game theory tools that will be an essential part of future works in the context of distributed radio resource management

Internet of Things (IoT) is an ecosystem comprises CT (Communication Technology),IT (Information Technology) and sometime OT (Operational Technologies) wheredifferent machines and devices can interact with each other and exchange useful datawhich can be processed using different IoT applications to take decisions and performrequired actions. Number of IoT devices and IoT networks are growing exponentially.Security is of utmost importance and without proper security implementation, IoTNetworks with billions of devices will be hacked and used as botnets which can createdisaster. The new IoT use cases cannot be realized using the current communicationtechnologies due to the QoS (Quality of Service) and business requirements. 5Gnetwork are designed keeping IoT use cases in mind and with the development of 5Gnetwork, it will be easier to implement more secured IoT network and enable differentIoT use cases which are not feasible today.To build the future IoT networks with 5G, it’s important to study and understand 5Gsecurity features. Security is perceived as one of the most important considerationwhile building IoT solutions and to implement 5G network for IoT solutions require anoverall understanding of 5G security features. In the thesis, work have been done toidentify the gap in the current research with respect to 5G security features anddescribe 5G features that will enhance IoT security. After identifying key 5G securityfeatures, the implementation of the identified 5G security features will be describedwith the 5G based smart grid and smart factory use cases. The key finding is howdifferent 5G security capabilities secure IoT communication and another importantfinding is that not all security capabilities are applicable to all IoT use cases. Hence,security capabilities to be used based on the 5G use case requirement.

The aim of this interdisciplinary work, with roots in business economics and engineering, is to propose a new and innovative business model starting from a description of existing business models enabled by 5G and 6G. The new business model, called the sharing platform business model (SPBM), is based on the concept of sharing economy and multi-sided business model. The SPBM exploits the advantages of a platform, which facilitates the collaboration and cooperation among all the stakeholders in the 5G ecosystem. The ongoing fifth generation of mobile networks has disrupted, in a positive way, the future wireless communication networks; the most significant novelty compared to previous generations is the capability of 5G to serve the requirements of the vertical industries. 5G and the future 6G are able to transform industries and to provide services at gigabit/s speeds, low latency and to open new business opportunities. The mobile ecosystem has completely changed, previous generations were based on voice and data services and business models characterized by a bilateral relationship between operators and their customers, on the other hand, 5G offers the opportunity to collaborate with vertical industries to provide new services for enterprises. Given these premises, there is a clear need for a complete change in business modelling to overcome traditional models and to pave the way for innovative business models, which shall be able to face the business transformation of the mobile ecosystem. One of the main factors responsible for the change in business modelling is the uncertainty regarding the network investors: while in traditional business models the investors were mainly the MNOs, in the new mobile ecosystem this aspect is unclear. The question is: who should invest in the network infrastructure? Probably the solution could be the creation of public-private partnerships but building a business model based on this premise is completely a novel exercise.

L'architecture de découpage du réseau en sous-réseaux "Network slicing", rendue possible grâce aux nouvelles technologies telles que la virtualisation des fonctions réseau (NFV) et le réseau défini par logiciel (SDN), est l'un des principaux piliers des réseaux 5G et au-delà (B5G). Dans les environnements de la cinquième génération et au-delà (B5G), on s'attend à une multiplication du nombre de sous-réseaux coexistant, plus ou moins complexes, avec des durées de vie, des besoins en ressources et des objectifs de performance très divers. Cela crée des défis importants pour la gestion et l'orchestration des sous-réseaux sans intervention humaine, y compris la sécurité, la gestion des pannes et la confiance. En outre, le découpage du réseau ouvre le marché à de nouvelles parties prenantes, à savoir le vertical ou le locataire, le fournisseur de tranches de réseau et le fournisseur d'infrastructure. Dans ce contexte, il est nécessaire d'assurer non seulement une interaction sécurisée entre ces acteurs, mais aussi que chaque acteur fournisse le service attendu pour répondre aux exigences des sous-réseaux. Il convient donc de concevoir de nouvelles architectures sécurisées capables d'identifier/détecter en temps réel les nouvelles formes d'attaques liées au découpage de réseaux en tranches, tout en gérant de manière sûre et automatique les accords de niveau de service (SLAs) entre les acteurs impliqués. Dans cette thèse, nous concevons une nouvelle architecture sécurisée adaptée aux réseaux prêts pour le "Network slicing" (réseaux de cinquième génération (5G) et au-delà), en nous appuyant fortement sur la blockchain et l'intelligence artificielle (IA) pour permettre une gestion sécurisée et fiable des sous-réseaux
Network slicing architecture, enabled by new technologies such as Network Functions Virtualization (NFV) and Software-Defined Networking (SDN), is one of the main pillars of Fifth-generation and Beyond (B5G). In B5G settings, the number of coexisting slices with varying degrees of complexity and very diverse lifespans, resource requirements, and performance targets is expected to explode. This creates significant challenges towards zero-touch slice management and orchestration, including security, fault management, and trust. In addition, network slicing opens the business market to new stakeholders, namely the vertical or tenant, the network slice provider, and the infrastructure provider. In this context, there is a need to ensure not only a secure interaction between these actors, but also that each actor delivers the expected service to meet the network slice requirements. Therefore, new trust architectures should be designed, which are able to identify/detect the new forms of slicing-related attacks in real-time, while securely and automatically managing Service Level Agreements (SLA) among the involved actors. In this thesis, we devise new security architectures tailored to network slicing ready networks (B5G), heavily relying on blockchain and Artificial Intelligence (AI) to enable secure and trust network slicing management

Location awareness is a key enabler for a variety of verticals and use cases (UCs) in 5th generation (5G) and beyond 5G (B5G) networks, including those related to autonomy, logistic, smart environments, and Industry 4.0. However, fulfilling the key performance indicator (KPI) requirements for such UCs is challenging. This calls for new localiztion algorithms able to learn from the environment and to fully leverage the positional information provided by the network measurements. Moreover, the integration of next generation cellular networks with sensor radar networks (SRNs), will be fundamental to further enhance these new verticals, as well as to improve the communication performance and the network resource management. This calls for an accurate modeling of the wireless impairments and the design of algorithms able to provide physical analytics (e.g., number of person in a monitored area) in addition to location information. The main objectives of this thesis are: 1. design of machine learning based algorithms for localization in 5G and B5G networks; and 2. characterization of wireless impairments in SRNs, as well as the design of algorithms for extracting physical analytics via SRNs. In particular, this thesis presents the design of soft information (SI)-based localiza- tion algorithms exploiting both radio access technology (RAT)-dependent (obtained from the 5G network) and RAT-independent (obtained via non-3rd Generation Partnership Project (3GPP) technologies) measurements. Performance using both SI and classical approaches are quantified in 3GPP standardized scenarios via rigorous simulations in full conformity with 3GPP technical specifications and reports. Results show that the pro- posed SI approach significantly outperforms the approaches reported in 3GPP technical reports. In addition, a statistical characterization of the clutter for SRNs employing ultra-wideband (UWB) signals is provided based on experimental measurements carried out in an indoor environment. Lastly, a crowd-centric counting algorithm based on machine learning techniques is proposed and compared with state-of-the-art approaches based on experimental measurements.

Network densification has become a dominant theme for capacity enhancement in cellular networks. However, it increases the operational complexity and expenditure for mobile network operators. Consequently, the essential features of Self-Organising Networks (SON) are considered to ensure the economic viability of the emerging cellular networks. This thesis focuses on quantifying the benefits of self-organisation in Cloud Radio Access Network (C-RAN) by proposing a flexible, energy efficient, and capacity optimised system. The Base Band Unit (BBU) and Remote Radio Head (RRH) map is formulated as an optimisation problem. A self-optimised C-RAN (SOCRAN) is proposed which hosts Genetic Algorithm (GA) and Discrete-Particle-Swarm-Optimisation algorithm (DPSO), developed for optimisation. Computational results based on different network scenarios demonstrate that DPSO delivers excellent performances for the key performance indicators compared to GA. The percentage of blocked users is reduced from 10.523% to 0.409% in a medium sized network scenario and 5.394% to 0.56% in a vast network scenario. Furthermore, an efficient resource utilisation scheme is proposed based on the concept of Cell Differentiation and Integration (CDI). The two-stage CDI scheme semi-statically scales the number of BBUs and RRHs to serve an offered load and dynamically defines the optimum BBU-RRH mapping to avoid unbalanced network scenarios. Computational results demonstrate significant throughput improvement in a CDI-enabled C-RAN compared to a fixed C-RAN, i.e., an average throughput increase of 45.53% and an average blocked users decrease of 23.149% is experienced. A power model is proposed to estimate the overall power consumption of C-RAN. Approximately 16% power reduction is calculated in a CDI-enabled C-RAN when compared to a fixed C-RAN, both serving the same geographical area. Moreover, a Divide-and-Sort load balancing scheme is proposed and compared to the SOCRAN scheme. Results show excellent performances by the Divide-and-Sort algorithm in small networks when compared to SOCRAN and K-mean clustering algorithm.

Recently, there has been a substantial growth in mobile data traffic due to the widespread of data hungry devices such as mobiles and laptops. The anticipated high traffic demands and low latency requirements stemmed from the Internet of Things (IoT) and Machine Type Communications (MTC) can only be met with radical changes to the network paradigm such as harnessing the millimetre wave (mmWave) band in Ultra-Dense Network (UDN). This thesis presents many challenges, problems and questions that arise in research and design stage of 5G network. The main challenges of 5G in mmWave can be characterised with the following attributes: i- huge traffic demands, with very high data rate requirements, ii- high interference in UDN, iii increased handover in UDN, higher dependency on Line of Sight (LOS) coverage and high shadow fading, and iv-massive MTC traffic due to billions of connected devices. In this work, software simulation tools have been used to evaluate the proposed solutions. Therefore, we have introduced 5G network based on network densification. Network densification includes densification over frequency through mmWave, and densification over space through higher number of antennas, Higher Order Sectorisation (HOS), and denser deployment of small-cells. Our results show that the densification theme has significantly improved network capacity and user Quality of Experience (QoE). UDN network can efficiently raise the user experience to the level that 5G vision promised. However, one of the drawback of using UDN and HOS is the significant increase in Inter-Cell Interference (ICI). Therefore, ICI has been addressed in this work to increase the gain of densification. ICI can degrade the performance of wireless network, particularly in UDN due to the increased interference from surrounding cells. We have used Fractional Frequency Reuse (FFR) as ICI Coordination (ICIC) for UDN network and HOS environment. The work shows that FFR has improved the network performance in terms of cell-edge data throughput and average cell throughput, and maintain the peak data throughput at a certain threshold. Additionally, HOS has shown even greater gain over default sectored sites when the interference is carefully coordinated. To generalise the principle of densification, we have introduced Distributed Base Station (DBS) as the envisioned network architecture for 5G in mmWave. Remotely distributed antennas in DBS architecture have been harnessed in order to compensate for the high path loss that characterise mmWave propagation. The proposed architecture has significantly improved the user data throughput, decreased the unnecessary handovers as a result of dense network, increased the LOS coverage probability, and reduced the impact of shadow fading. Additionally, this research discusses the regulatory requirements at mmWave band for the Maximum Permissible Exposure (MPE). Finally, scheduling massive MTC traffic in 5G has been considered. MTC is expected to contribute to the majority of IoT traffic. In this context, an algorithm has been developed to schedule this type of traffic. The results demonstrate the gain of using distributed antennas on MTC traffic in terms of spectral efficiency, data throughput, and fairness. The results show considerable improvement in the performance metrics. The combination of these contributions has provided remarkable increase in data throughput to achieve the 5G vision of “massive” capacity and to support human and machine traffic.

The massive proliferation of sophisticated mobile terminals with advanced capabilities have led to an enormous surge in the demand for mobile broadband data. Also, the recent popularity of bandwidth intensive applications such as Netflix and YouTube has contributed to this demand for the wireless resources. In order to cope with this massive demand, fifth generation (5G) of wireless network is on the verge of deployment. This new generation of the wireless networks would pose different challenges for both subscribers and service providers, and the challenges need to be carefully addressed. Due to the diverse nature of the subscribers of mobile broadband, one network element is inadequate to meet the imposed requirements. Subscribers vary in terms of their usage of wireless resources as well as their preferred content. Deployment of the 5G systems promises the introduction of multiple tiers of heterogeneous networks within its architecture. This means radio access technologies (RATs) of various kinds (2G, 3G, 4G, 5G and Wi-Fi) would have to co-exist and aim to bridge the gap between the supply and demand for data. Subscribers, equipped with multi-mode or multi homing mobile terminals, can connect to one or more RATs to receive the required services. They also often run multiple applications simultaneously and as such, it must be ensured that the best access technology is assigned to a particular subscriber to maintain quality of experience and service. As such, an algorithm need to be devised that selects the best network to provide ubiquitous coverage to different types of users, running various kinds of applications, under dynamic network conditions. The network and infrastructure providers, on the other hand, face the need to meet up with the demand for data that the subscribers in different coverage regions require. In the 5G system, traditional proprietary hardware performing dedicated network functions such as packet gateway and service gateway would be replaced by softwarized virtual network functions (VNFs). These VNFs would need to be hosted in the data centres and would require computational power to process the subscribers’ traffic originating in an area. Therefore, data centres are set to play a key role in the provisioning of service in 5G systems. However, before establishing a data centre in a region, the traffic profile of that region need to be carefully studied to determine the optimal position and dimension of the facility. Furthermore, as cellular traffic differs depending on the time of the day, accurate prediction models are required to forecast future traffic demand to ensure dynamic and proper utilization of resources. This thesis aims to propose solutions to address these problems that subscribers and infrastructure providers face. Firstly, an algorithm is proposed to select the best access network for a subscriber running single or group of applications. Deviating from the existing access selection schemes in the literature, which consider the RAT-selection problem in an environment where accurate information is always available, the proposed algorithm models the problem in a completely fuzzy environment. As wireless networks are highly dynamic systems that are not only very unpredictable but also susceptible to sudden changes (for example malfunction of a particular RAT rendering it unusable), fuzzy systems are most adept in representing them. In the proposed algorithm, a new branch of fuzzy logic, Intuitionistic Fuzzy (IF) logic, is used with a popular multi-criteria decision making (MCDM) algorithm -Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), to formulate a network selection problem. The IF-TOPSIS scheme is designed to accurately take in various parameters such as network conditions, different number of applications and user preferences to select the ideal network for different types of subscribers. The second part of this thesis aims to solve the problem associated with establishment of data centre and utilization of its resources. As the cellular traffic exhibit strong spatial and temporal dependencies, it becomes necessary to analyse the traffic before establishing an infrastructure like a data centre. Existing literature do not consider real world traffic while determining the best location and dimension of 5G data centres. In this thesis, a real world traffic data set is first analysed to understand the variations that are present in different regions within a city. Based on the traffic analysis, the ideal placement of the data centre is formulated as a facility location problem and solved using the Weiszfeld’s algorithm. Additionally, based on the traffic analysis, the optimal dimensions of the data centre in different regions are heuristically obtained. Finally, machine learning algorithms are employed to obtain future traffic demand values to aid dynamic allocation of data centre resources. Simulation results are presented to show the effectiveness of the proposed schemes.

Abstract. High degree of flexibility, customization and the rapid deployment methods are needed in future communication systems required by different vertical sectors. These requirements will be beyond the traditional mobile network operators’ offerings. The novel concept called micro-operator enables a versatile set of stakeholders to operate local 5G networks within spatially confined environment with a guaranteed quality and reliability to complement mobile network operators’ offerings. To enable the case specific requirements of different stakeholders, micro-operator architecture should be tailored to cater such requirements, so that the service is optimized. The novel micro-operator architecture proposed in this thesis using 5G access and core network functions, serves the communication needs of an Industry 4.0 environment having three use cases namely augmented reality, massive wireless sensor networks and mobile robots. Conceptual design of the proposed architecture is realized using simulation results for latency measurements, relating it with the results of a mobile network operator-based deployment. Latency analysis is carried out with respect to the core network distance and the processing delay of core network functions. Results demonstrate the advantages of the micro-operator deployment compared with mobile network operator deployment to cater specialized user requirements, thereby concluding that the micro-operator deployment is more beneficial.

The current advancements of communication systems and their applications have changed our lives and will influence them further in the future. Next generation 5G networks will represent a salient technological breakthrough that combines old and new technologies and involves, among all, new models of service provisioning and resource sharing. In particular, they will lead to the emergence of mechanisms and architectures towards the on-demand multi-tenant philosophy. In this new eco- system, it will be necessary to address the trust question among stakeholders as well as their security. The 5G revolution brings new pitfalls due to novel forms of human-to-device in- teractions and the even higher pervasiveness of the technology in human life. As an example, in the Internet of Things (IoT), devices equipped with sensing, processing, storage and decision-making capabilities, can actively interact with one another and with humans. Although their design could strictly adhere to the principles of pri- vacy and security, several factors, such as weak implementations of communication protocols, metadata information exchange, and architectural flaws, could jeopardise the security and privacy of their owners. Moreover, the augmented complexity and heterogeneity deriving from the ultra-densification of communication infrastructures, although it can improve data rate, reduce delay, and coverage of cellular networks, might raise new threats to the privacy of network subscribers. In the first part of this thesis, we provide an overview of 5G networks and analyse the security, trust, and privacy problems in it. Then, we discuss the mutual impact of security and privacy of stakeholders and the use of semantic reasoning systems for the trust evaluation. In this vein, we studied the features of security ontologies that can influence the automated threat identification process and laid out a road towards ontologies simplification. In the second part of this thesis, we give a brief introduction to the privacy issues in the IoT. Then, we propose a methodology of analysis for identification of privacy threats in the IoT which can explore the privacy issue space from different perspectives and at various levels of abstraction. In the third part of this thesis, we explore the effect of both user equipment and access points densification on the location privacy. We characterised the relationship between density of users and the success of at- tacks aiming at disclosing the location of subscribers. Hence, we propose a mitigation strategy founded on the concept of virtual cells.

Time Sensitive Networking (TSN) defined in the IEEE 802.1 working group, is an important enabler for industrial Internet of things, specifically industry 4.0. 3GPP release 16 specifications includes the 5G system as a logical TSN bridge, thus promoting the integration of 5G technology with TSN. This combination provides wireless deterministic communication thus ensuring low, bounded delay and near-zero packet loss. In this thesis, we implement a 5G system in- tegration with TSN using a discrete event network simulator (NS-3). Further, we propose a simplified per egress port scheduling algorithm based on IEEE 802.1Q (scheduled traffic standard) running in the Centralized Network Con- troller (CNC). Average packet delay, average jitter, average throughput and the packet loss is measured for comparing the performance difference when our TSN scheduler is used versus when it is not. The designed system is tested by measuring it’s network impact in terms of average delay and packet loss. The 5GS logical bridge behavior is simulated by varying the 5G bridge de- lay dynamically. For every frame transmission in the queue, the processing delay of a particular bridge is varied with pre-defined set of values. Two sets of 5GS bridge delay variations are considered, i.e. between 1-10ms and 5- 10ms respectively. On calculating the network impact, we conclude that the overall impact on the network decreases as the variation range for the delay gets smaller. This proves that higher delay variations have a significant impact whereas smaller delay variations have a negligible impact on the network. For the latter case, the system delay is considerably stable and thus can be used for industrial applications in real-life TSN scenarios.
Tidskritiska nätverk (TSN) definierat i IEEE 802.1-arbetsgruppen, är en vik- tig faktor för det industriella Sakernas Internet, särskilt när det gäller Industri4.0. Specifikationer enligt 3GPP release 16 inkluderar 5G-system som en lo- gisk TSN-brygga, som främjar integrationen av 5G-teknik med TSN. 5G med TSN ger trådlös deterministisk kommunikation som säkerställer låg, begrän- sad fördröjning och nästan noll paketförlust. I denna rapport implementerar vi en 5G-systemintegration med TSN med hjälp av en diskret händelse simu- lator (NS-3). Dessutom föreslår vi en förenklad algoritm för schemaläggning av portar per utgång baserat på IEEE 802.1Q (Scheduled Traffic Standard) som körs i en centraliserad nätverks-controller (CNC). Genomsnittlig paket- fördröjning, genomsnittlig fördröjningsvariation, genomsnittlig genomström- ning och paketförlust mäts för att jämföra prestandaskillnaden när vår TSN- schemaläggare används jämfört med när den inte används. Det utformade sy- stemet testas genom att mäta nätverkets påverkan i termer av genomsnittlig fördröjning och paketförlust. 5GS logiska bryggbeteende simuleras genom att dynamiskt variera 5G-bryggfördröjningen. För varje bildöverföring varieras bryggans bearbetningsfördröjning med en fördefinierad uppsättning värden. Två fördefinierade uppsättningar av 5GS-fördröjningsvariationer beaktas som ligger mellan 1-10ms respektive 5-10ms. När vi beräknar nätverkspåverkan drar vi slutsatsen att den totala effekten på nätverket minskar när variationen i fördröjningen blir mindre. Detta visar att högre fördröjningsvariationer har en signifikant effekt medan mindre fördröjningsvariationer har en försumbar effekt. I det senare fallet är systemfördröjningen betydligt stabilare och kan användas för tillämpningar i verkliga TSN-scenarier.

This thesis investigates resource management procedures, within the Multi-access Edge Computi ng (MEC) paradigm, to obtain energy savings and guarantee Quality of Service(QoS) in Mobile Networks (MNs). Here, we enable energy savings within green-aware network apparatuses (i.e., communication and computing facilities) through the application of learning and control techniques, together with energy management procedures (BS sleep mode, VM soft-scaling, tuning of transmission drivers). In this study, we consider the MEC deployment scenarios suggested by ETSI and mobile operators for our system models. Firstly, we investigate energy-saving strategies within a remote site fully powered by only green/renewable energy (solar and wind). Here, we consider a single Base Station (BS) co-located with the MEC server, i.e., the BS is empowered with computing capabilities. To address the energy consumption problem within the remote site, we propose an online algorithm for edge network management. The algorithm make use of a Long Short-Term Memory (LSTM) neural network for estimating the short-term future traffic load and harvested energy, and control theory, specifically the Limited Lookahead Control (LLC) principles, for foresighted optimization. It also make use of energy management procedures, i.e., BS sleep modes and Virtual Machine (VM) soft-scaling (the reduction of computing resources per time instance). To obtain the energy savings and guarantee QoS, per time instance, the algorithm considers the future BS loads, onsite green energy available and then provisions edge network resources based on the learned information. Secondly, we study the energy consumption problem within an environment where BSs are densely-deployed, i.e., similar to an urban or semi-urban scenario. This work extend the energy consumption problem from a single BS case to multiple BSs. Here, each BS is powered by hybrid energy supplies (solar and power grid) and also empowered with computation capabilities (each BS is co-located with a MEC server). Towards edge system management, we propose a controller-based network architecture for managing energy harvesting (EH) BSs empowered with computation capabilities where on/off switching strategies allow BSs and VMs to be dynamically switched on/off, depending on the traffic load and the harvested energy forecast, over a given look-ahead prediction horizon. To solve the energy consumption minimization problem in a distributed manner, the controller partitions the BSs into clusters based on their location; then, for each cluster, it minimizes a cost function capturing the individual communication site energy consumption and the users’ QoS. To manage the communication sites, the controller performs online supervisory control by forecasting the traffic load and the harvested energy using a LSTM neural network, which is utilized within a LLC policy to obtain the system control actions that yield the desired trade-off between energy consumption and QoS. Finally, we investigate the energy consumption problem within a virtualized MEC server placed in proximity to a group of BSs. To address this challenge, we consider a computing-plus-communication energy model, within the MEC paradigm, where we focus on the communication-related energy cost in addition to the energy drained due to computing processes. Towards server management, an online algorithm based on traffic engineering and MEC Location Service is proposed. To obtain the energy savings and QoS guarantee, we jointly launch an optimal number of VMs for computing and transmission drivers coupled with the location-aware traffic routing for real-time data transfers. In order to efficiently provisioned edge system resources, we forecast the server workloads and harvested energy by using a LSTM neural network and the output is then used within the LLC-based algorithm. Our numerical results, obtained through trace-driven simulations, show that the proposed optimization strategies (algorithms) leads to a considerable reduction in the energy consumed by the edge computing and communication facilities, promoting energy self-sustainability within the MN through the use of green energy.