No / Conventional Call Admission Control (CAC) schemes are based on stand-alone Radio Access Networks (RAN) Base Station (BS) architectures which have their independent and fixed spectral and computing resources, which are not shared with other BSs to address their varied traffic needs, causing poor resource utilization, and high call blocking and dropping probabilities. It is envisaged that in future communication systems like 5G, Cloud RAN (C-RAN) will be adopted in order to share this spectrum and computing resources between BSs in order to further improve the Quality of Service (QoS) and network utilization. In this paper, an intelligent Elastic CAC scheme using Fuzzy Logic in C-RAN is proposed. In the proposed scheme, the BS resources are consolidated to the cloud using virtualization technology and dynamically provisioned using the elasticity concept of cloud computing in accordance to traffic demands. Simulations shows that the proposed CAC algorithm has high call acceptance rate compared to conventional CAC.

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Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2018-11-05T14:23:30Z No. of bitstreams: 2 Dissertação - Phelipe Alves de Souza - 2018.pdf: 2593287 bytes, checksum: 75272a4ac609ad844ce539216911cb72 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-11-05T14:30:42Z (GMT) No. of bitstreams: 2 Dissertação - Phelipe Alves de Souza - 2018.pdf: 2593287 bytes, checksum: 75272a4ac609ad844ce539216911cb72 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-11-05T14:30:42Z (GMT). No. of bitstreams: 2 Dissertação - Phelipe Alves de Souza - 2018.pdf: 2593287 bytes, checksum: 75272a4ac609ad844ce539216911cb72 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-10-05 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / There are great expectations in CRAN and network virtualization (NFV) technologies, and especially in view of the potential they have to accelerate the deployment of new services while lowering the costs of network operators. Several papers discussed the benefits of deploying a new network infrastructure with such technologies, but only a few investigated how the transition from a legacy network could be. In this context, there is a relevant problem that involves three main issues: 1) which network locations should be updated; 2) how to update the selected location, \ie, to fully virtualized or not; and 3) who should attend virtualized sites. These issues are influenced by the level of centralization employed in a given access network (RAN). Here we propose two optimization models and two heuristics that allow the decision maker to define the desired level of centralization and to evaluate its impact on some metrics such as the investment needed and the level of centralization actually achieved. The models show how the investment should be applied according to the level of centralization and the relative cost between the different resources. Our heuristics present similar performance to the exact approach for relatively small scenarios of the problem, but are able to solve topologies of networks with large number of vertices and maintain a satisfactory solution close to the ideal. / Existem grandes expectativas nas tecnologias de centralização (CRAN) e de virtualização de rede (NFV), e especialmente diante do potencial que têm de acelerar a implantação de novos serviços e, ao mesmo tempo, diminuir os custos das operadoras de redes. Vários trabalhos discutiram os benefícios de se implantar uma nova infraestrutura de rede, com tais tecnologias, mas apenas alguns investigaram como poderia ser a transição a partir de uma rede legada. Nesse contexto, existe um problema relevante que envolve três questões principais: 1) quais locais da rede devem ser atualizados; 2) como atualizar o local selecionado, \ie, para totalmente virtualizado ou não; e 3) quem deve atender aos locais virtualizados. Essas questões são influenciadas pelo nível de centralização empregado em uma determinada rede de acesso (RAN). Aqui, propomos dois modelos de otimização e duas heurísticas que permitem ao tomador de decisão definir o nível de centralização desejado e avaliar seu impacto em algumas métricas, tais como o investimento necessário e o nível de centralização efetivamente alcançado. Os modelos mostram como o investimento deve ser aplicado de acordo com o nível de centralização e o custo relativo entre os diferentes recursos. Nossas heurísticas apresentam desempenho semelhante à abordagem exata para cenários relativamente pequenos do problema, mas são capazes de resolver topologias de redes com grande número de vértices e manter uma solução satisfatória próxima ao ideal.

Le réseau d'accès radio centralisé (C-RAN) peut fortement augmenter la capacité des réseaux mobiles. Cependant, la faisabilité de C-RAN est limitée par le débit considérable engendré sur les liaisons de transport, appelées également fronthaul. L'objectif de cette thèse est d'améliorer les performances de C-RAN tout en considérant les limitations du débit sur le frontaul, l'allocation de ressources et l'ordonnancement des utilisateurs.Nous étudions d'abord les séparations fonctionnelles possibles entre les têtes radios distantes (RRH) et les unités de traitement en bande de base (BBU) sur la liaison montante pour réduire le débit de transmission sur le fronthaul : certaines fonctions de couche basse sont déplacées du BBU vers les RRH. Nous fournissons une analyse quantitative des améliorations de performances ainsi obtenues.Nous nous concentrons ensuite sur la transmission coordonnée Multi-point (CoMP) sur le lien descendant. CoMP peut améliorer l'efficacité spectrale mais nécessite une coordination inter-cellule, ce qui est possible uniquement si une capacité fronthaul élevée est disponible. Nous comparons des stratégies de transmission avec et sans coordination inter-cellule. Les résultats de simulation montrent que CoMP doit être préféré pour les utilisateurs situés en bordure de cellule et lorsque la capacité du fronthaul est élevée. Nous en déduisons une stratégie hybride pour laquelle Les utilisateurs sont divisés en deux sous-ensembles en fonction de la puissance du signal. Les utilisateurs situés dans les zones centrales sont servis par un seul RRH avec une coordination simple et ceux en bordure de cellule sont servis en mode CoMP. Cette stratégie hybride constitue un bon compromis entre les débits offerts aux utilisateurs et les débits sur le fronthaul. / Centralized/Cloud Radio Access Network (C-RAN) is a promising mobile network architecture, which can potentially increase the capacity of mobile networks while reducing operators¿ cost and energy consumption. However, the feasibility of C-RAN is limited by the large bit rate requirement in the fronthaul. The objective of this thesis is to improve C-RAN performance while considering fronthaul throughput reduction, fronthaul capacity allocation and users scheduling.We first investigate new functional split architectures between Remote Radio Heads (RRHs) and Baseband Units (BBU) on the uplink to reduce the transmission throughput in fronthaul. Some low layer functions are moved from the BBU to RRHs and a quantitative analysis is provided to illustrate the performance gains. We then focus on Coordinated Multi-point (CoMP) transmissions on the downlink. CoMP can improve spectral efficiency but needs tight coordination between different cells, which is facilitated by C-RAN only if high fronthaul capacity is available. We compare different transmission strategies without and with multi-cell coordination. Simulation results show that CoMP should be preferred for users located in cell edge areas and when fronthaul capacity is high. We propose a hybrid transmission strategy where users are divided into two parts based on statistical Channel State Informations (CSIs). The users located in cell center areas are served by one transmission point with simple coordinated scheduling and those located in cell edge areas are served with CoMP joint transmission. This proposed hybrid transmission strategy offers a good trade-off between users¿ transmission rates and fronthaul capacity cost.

De nos jours, l’architecture du réseau mobile est en pleine évolution pour assurer la montée en débit entre les Centraux (CO) (réseaux coeurs) et différents terminaux comme les mobiles, ordinateurs, tablettes afin de satisfaire les utilisateurs. Pour faire face à ces défis du futur, le réseau C-RAN (Cloud ou Centralized-RAN) est connu comme une solution de la 5G. Dans le contexte C-RAN, toutes les BBUs (Base Band Units) sont centralisées dans le CO, seules les RRH (Remote Radio Head) restent situées à la tête de la station de base (BS). Un nouveau segment entre les BBUs et RRHs apparait nommé « fronthaul ». Il est basé sur des transmissions D-ROF (digital radio-overfiber) et transporte le signal radio numérique à un débit binaire élevé en utilisant le protocole CPRI (Common Public Radio Interface). En prenant en compte le CAPEX et l’OPEX, le projet ANR LAMPION a proposé la technologie RSOA (Reflective Semiconductor Optical Amplifier) auto alimenté afin de rendre la solution plus flexible et s’affranchir d’émetteurs/récepteurs colorés dans le cadre de transmission WDM-PON (Wavelength Division Multiplexing Passive Optical Network). Néanmoins, il est nécessaire d’ajouter un FEC (forward error corrector) dans la transmission pour assurer la qualité de service. Donc l’objectif de cette thèse est de trouver le FEC le plus adéquat à appliquer dans le contexte C-RAN. Nos travaux se sont focalisés sur l’utilisation de codes LDPC, choisis après comparaisons des performances avec les autres types de codes. Nous avons précisé les paramètres (rendement du code, taille de la matrice, cycle, etc.) nécessaires pour les codes LDPC afin d'obtenir les meilleures performances. Les algorithmes LDPC à décisions dures ont été choisis après considération du compromis entre complexités de circuit et performance. Parmi ces algorithmes à décision dures, le GDBF (gradient descent bit-flipping) était la meilleure solution. La prise en compte d’un CAN 2-Bit dans le canal nous a amené à proposer une variante : le BWGDBF (Balanced weighted GDBF). Des optimisations ont également été faites en regard de la convergence de l'algorithme et de la latence. Enfin, nous avons réussi à implémenter notre propre algorithme sur le FPGA Spartan 6 xc6slx16. Plusieurs méthodes ont été proposées pour atteindre une latence de 5 μs souhaitée dans le contexte C-RAN. Cette thèse a été soutenue par le projet ANR LAMPION (Lambada-based Access and Metropolitan Passive Optical networks). / Nowadays, the architecture of the mobile network is in full evolution to ensure the increase in terms of bit rate between the Central (CO) (core networks) and various terminals such as mobiles, computers, tablets in order to satisfy the users. To address these challenges of the future, the C-RAN (Cloud or Centralized-RAN) network is known as a 5G solution. In the C-RAN context, all BBUs (Base Band Units) are centralized in the CO, only the RRH (Remote Radio Head) remain at the head of the base station (BS). A new segment between BBUs and RRHs appears called "fronthaul". It is based on D-ROF (digital radio-overfiber) transmissions and carries the digital radio signal at a high bit rate using the Common Public Radio Interface (CPRI) protocol. Taking into account CAPEX and OPEX, the ANR LAMPION project has proposed the Self-seeded Reflective Semiconductor Optical Amplifier (RSOA) technology in order to make the solution more flexible and overcome the need for colored transmitters / receivers in the context of PON-WDM (Wavelength Division Multiplexing Passive Optical Network). Nevertheless, it is necessary to add a FEC (forward error corrector) in the transmission to ensure the quality of service. So the objective of this thesis is to find the most suitable FEC to apply in the C-RAN context. Our work has focused on the use of LDPC codes, chosen after performance comparisons with other types of codes. We have specified the parameters (code performance, matrix size, cycle, etc.) required for LDPC codes to obtain the best performance. Hard-decision LDPC algorithms were chosen after considering the tradeoff between circuit complexities and performance. Among these hard-decision algorithms, the GDBF (gradient descent bit-flipping) was the best solution. Taking into account a CAN 2-Bit in the channel led us to propose a variant: the BWGDBF (Balanced weighted GDBF). Optimizations have also been made with respect to the convergence of the algorithm and latency. Finally, we managed to implement our own algorithm on the Spartan FPGA 6 xc6slx16. Several methods have been proposed to achieve a latency of 5 μs desired in the C-RAN context. This thesis was supported by the project ANR LAMPION (Lambada-based Access and Metropolitan Passive Optical Networks).

Cette these est composee de deux parties independantes ayant pour point commun l’utilisation intensive de la theorie des ∞-categories. Dans la premiere, on s’interesse aux liens entre deux approches differentes de la formalisation de la physique des particules : les algebres vertex et les algebres a factorisation a la Costello. On montre en particulier que dans le cas des theories dites topologiques, elles sont equivalentes. Plus precisement, on montre que les∞-categories de fibres vectoriels factorisant non-unitaires sur une variete algebrique complexe lisse X est equivalente a l’∞-categorie des EM-algebres non-unitaires et de dimension finie, ou M est la variete topologique associee a X. Dans la seconde, avec Mathieu Anel, nous etudions la caracterisation de l’exponentiabilite dans l’∞-categorie des ∞-topos. Nous montrons que les ∞-topos exponentiables sont ceux dont l’∞-categorie de faisceaux est continue. Une consequence notable est que l’∞-categorie des faisceaux en spectres sur un ∞-topos exponentiable est un objet dualisable de l’∞-categorie des ∞-categories cocompletes stables munie de son produit tensoriel. Ce chapitre contient aussi une construction des ∞-coends a partir de la theorie du produit tensoriel d’∞- categories cocompletes, ainsi qu’une description des ∞-categories de faisceaux sur un ∞-topos exponentiable en termes de faisceaux de Leray. / This thesis is made of two independent parts, both relying heavily on the theory of ∞-categories. In the first chapter, we approach two different ways to formalize modern particle physics, through the theory of vertex algebras and the theory of factorisation algebras a la Costello. We show in particular that in the case of ‘topological field theories’, they are equivalent. More precisely, we show that the ∞-category of non-unital factorization vector bundles on a smooth complex variety X is equivalent to the ∞-category of non-unital finite dimensional EM-algebras where M is the topological manifold associated to X. In the second one, with Mathieu Anel, we study a characterization of exponentiable objects of the∞-category of∞-toposes.We show that an ∞-topos is exponentiable if and only if its ∞-category of sheaves of spaces is continuous. An important consequence is the fact that the ∞-category of sheaves of spectra on an exponentiable ∞-topos is a dualisable object of the ∞-category of cocontinuous stable ∞-categories endowed with its usual tensor product. This chapter also includes a ix construction of∞-coends from the theory of tensor products of cocomplete∞- categories, together with a description of∞-categories of sheaves on exponentiable ∞-toposes in terms of Leray sheaves.

Le Cloud Radio Access Network (C-RAN) est une future direction dans les réseaux de communications sans fils pour déployer des systèmes cellulaires 4G et renforcer la migration des opérateurs vers la nouvelle génération 5G. En comparaison avec l'architecture traditionnelle des stations de base distribuées, l'architecture C-RAN apporte un lot d'avantages à l'opérateur: meilleure utilisation des ressources radio, flexibilité du réseau, minimisation de la puissance consommée et amenuisement des coûts de déploiement. Dans cette thèse, nous adressons le problème d'allocation dynamique des ressources et minimisation de la puissance des communications à liaison descendante dans le C-RAN. Notre recherche vise à allouer les ressources radio à des flux dynamiques d'utilisateurs, tout en trouvant les meilleures combinaisons entre points d'accès et unités de calculs, pour satisfaire la demande de trafic. Il s'agit en outre, d'un problème d'optimisation non linéaire et NP-difficile, comprenant plusieurs contraintes relatives aux demandes de ressources des utilisateurs, gestion d'interférences, capacités fixes des unités de calcul dans le Cloud et des liaisons de transport ainsi que la limitation de la puissance transmise maximale. Afin de surmonter la complexité inhérente à cette problématique du C-RAN, nous présentons différentes approches pour l'allocation dynamique des ressources en trois principales contributions. Les résultats de nos simulations prouvent l'efficacité de nos méthodes, comparé à celles existantes dans la littérature, en termes de taux de débit de satisfaction, nombre d'antennes actives, puissance consommée dans le Cloud, résilience et coût opérationnel du C-RAN. / Cloud Radio Access Network (C-RAN) is a future direction in wireless communications for deploying cellular radio access subsystems in current 4G and next-generation 5G networks. In the C-RAN architecture, BaseBand Units (BBUs) are located in a pool of virtual base stations, which are connected via a high-bandwidth low latency fronthaul network to Radio Remote Heads (RRHs). In comparison to standalone clusters of distributed radio base stations, C-RAN architecture provides significant benefits in terms of centralized resource pooling, network flexibility and cost savings. In this thesis, we address the problem of dynamic resource allocation and power minimization in downlink communications for C-RAN. Our research aims to allocate baseband resources to dynamic flows of mobile users, while properly assigning RRHs to BBUs to accommodate the traffic and network demands. This is a non-linear NP-hard optimization problem, which encompasses many constraints such as mobile users' resources demands, interference management, BBU pool and fronthaul links capacities, as well as maximum transmission power limitation. To overcome the high complexity involved in this problem, we present several approaches for resource allocation strategies and tackle this issue in three stages. Obtained results prove the efficiency of our proposed strategies in terms of throughput satisfaction rate, number of active RRHs, BBU pool processing power, resiliency, and operational budget cost.

The advent of the fifth generation mobile networks (5G) presents many new challenges to satisfy the requirements of the upcoming standards. The 5G Radio Access Network (RAN) has several functions which must be highly optimized to keep up with increasing performance requirements. One such function is the Packet Processing Function (PPF) which must process network packets with high throughput and low latency. A major factor in the pursuit of higher throughput and lower latency is adaptability of 5G technology. For this reason, Ericsson has developed a prototype 5G RAN PPF as a Virtualized Network Function (VNF) using an extended version of the Data Plane Development Kit’s Eventdev framework, which can be run on a general purpose computer. This thesis project optimizes the throughput and latency of a 5G RAN PPF prototype using a set of benchmarking and code profiling tools to find bottlenecks within the packet processing path, and then mitigates the effects of these bottlenecks by changing the configuration of the PPF. Experiments were performed using IxNetwork to generate 2 flows with GTP-u/UDP/IPv4 packets for the PPF to process. IxNetwork was also used to measure throughput and latency of the PPF. The results show that the maximum throughput of the PPF prototype could be increased by 40.52% with an average cut-through latency of 97.59% compared to the default configuration in the evaluated test case, by reassigning the CPU cores, performing the packet processing work in fewer pipeline stages, and patching the RSS function of the packet reception (Rx) driver. / Med den annalkande femte generationen av mobila nätverk (5G) följer en rad utmaningar för att uppnå de krav som ställs av kommande standarder. Den femte generationens Radioaccessnätverk (RAN) har flera funktioner som måste vara väloptimerade för att prestera enligt ökade krav. En sådan funktion är Packet Processing-funktionen (PPF), vilken måste kunna bearbeta paket med hög genomströmning och låg latens. En avgörande faktor i jakten på högre genomströmning och lägre latens är anpassningsbarhet hos 5Gteknologin.  Ericsson har därför utvecklat en prototyp av en PPF för 5G RAN som en virtuell nätverksfunktion (VNF) med hjälp av DPDK:s Eventdev-ramverk, som kan köras på en dator avsedd för allmän användning. I detta projekt optimeras genomströmningen och latensen hos Ericssons 5G RAN PPF-prototyp med hjälp av ett antal verktyg för prestandamätning och kodprofilering för att hitta flaskhalsar i pakethanteringsvägen, och därefter minska flaskhalsarnas negativa effekt på PPFens prestanda genom att ändra dess konfiguration. I experimenten användes IxNetwork för att generera 2 flöden med GTP-u/UDP/IPv4-paket som bearbetades av PPFen. IxNetwork användes även för att mäta genomströmning och latens. Resultaten visade att den maximala genomströmningen kunde ökas med 40.52% med en genomsnittlig latens på 97.59% jämfört med den ursprungliga PPF-prototypkonfigurationen i testfallet, genom att omfördela processorkärnor, sammanslå paketbearbetningssteg, och att patcha RSS-funktionen hos mottagardrivaren.

De riskfaktorer som kan mätas eller avgöras i förskolan kan bara delvis förutsäga omfattningen av kommande lässvårigheter. Dessutom finns en påtaglig ärftlig komponent som sannolikt påverkar omfattningen av behovet av undervisningsinsats. De faktorer som kan ge en antydan om kommande lässvårigheter och som en förskolepedagog enkelt kan skapa lekar kring och bedöma är: RAN, förmågan att kunna skriva det egna namnet, hittepåord och bokstäver, koncentrationssvårigheter, finmotorisk koordination och kanske förmågan att uttala nonsensord. Pojkar har en högre risk. För att öka möjligheten att tidigt identifiera förskolebarn i riskzonen för kommande lässvårigheter skulle lästräning kunna påbörjas i förskoleklass (6-års-klass). Detta gäller oavsett om barnet har läs-svårigheter eller ej. De valda metoderna för läsinlärning bör vara olika i början av lästräningen jämfört med längre upp i åldrarna. Befintlig forskning tyder på att barn som börjar lära sig läsa i första hand behöver träna fonologisk medvetenhet och att phonics är en viktig metod i denna träning, men att ’hjärnans fonologiska mognad’ gör nyttan tveksam för barn yngre än 6 år – särskilt om dessa barn är pojkar. Spännvidden av orsaker, och att läsförmågan både kan förbättras och försämras över tid, tyder dock på att riskidentifiering i förskolan inte räcker till och att det sannolikt enda sättet att säkerställa adekvat utbildning till barn med lässvårigheter är kontinuerliga och tätt återkommande mätningar av hur väl barn tar till sig grundskoleundervisningen i läsning. Genom mätningarna kan utbildningen löpande justeras och anpassas till barnets behov här och nu. Över huvud taget uppvisar resultaten från tvillingstudier och från longitudinella studier att lästillägnandet har stora likheter med träning i sporter och musikinstrument: först måste grunden nötas in, varefter förmågan senare förfinas genom tålmodig och allt svårare upprepning. Detta är än viktigare för barn med lässvårigheter. Den fortlöpande försämringen av PISA-resultaten kommer inte att kunna brytas av åtgärder i förskolan eller genom systematisk satsning på phonics, utan det handlar om den politiska viljan finns inom det svenska skolväsendet för att ge alla barn samma chans i livet.

Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2018-11-13T11:19:19Z No. of bitstreams: 1 Leandro Andrioli_.pdf: 6621163 bytes, checksum: b4a58154b0441ad094c57bbbea979ac4 (MD5) / Made available in DSpace on 2018-11-13T11:19:20Z (GMT). No. of bitstreams: 1 Leandro Andrioli_.pdf: 6621163 bytes, checksum: b4a58154b0441ad094c57bbbea979ac4 (MD5) Previous issue date: 2018-07-31 / Nenhuma / Até o ano de 2020, espera-se que a área de cobertura das redes de celulares aumente em 10 vezes, com mais de 50 bilhões de dispositivos conectados, suportando 100 vezes mais equipamentos de usuários e elevando a capacidade da taxa de dados em 1000 vezes. Tal circunstância gerará um aumento massivo no tráfego de dados, fomentando o desenvolvimento da 5G e fazendo com que a indústria e as iniciativas científicas passem a voltar seus esforços para atender a essa demanda. Ganha força, então, as pesquisas relacionadas a Cloud Radio Access Networks (C-RANs), uma arquitetura que consolida as base stations (BSs) para um ponto centralizado na nuvem, mudando a ideia de atuar com recursos fixos e limitados, na medida em que se beneficia de uma das características chave da Computação em Nuvem: a elasticidade de recursos. Um dos grandes desafios na arquitetura C-RAN reside na complexidade em orquestrar todos esses recursos computacionais de forma que o processamento das requisições seja realizado com alto desempenho e com o menor custo de infraestrutura possível. Diante de todo esse contexto, a presente dissertação busca desenvolver o modelo Elastic-RAN, propondo um conceito de elasticidade multinível não bloqueante, com orquestração automática de recursos através da coordenação de BBU Pools e seus BBUs, junto a um mecanismo de grão elástico adaptativo. A elasticidade multinível não bloqueante permite controlar o nível de BBU Pool (máquina física), haja vista o alto volume de tráfego e a distância máxima sugerida entre as antenas e os pools, e o nível de BBU (máquina virtual), em razão do alto processamento de CPU e memória necessária para as requisições, de modo a não penalizar os processamentos correntes. O mecanismo de grão elástico adaptativo permite provisionar e mapear os recursos sob demanda e em tempo de execução, considerando o uso corrente dos recursos, para que cada ação elástica seja executada com um grão próximo das necessidades correntes de processamento. O modelo Elastic-RAN foi avaliado por intermédio de experimentos que simularam diferentes perfis de cargas, os quais são executados em uma aplicação intensiva de CPU e de tráfego na rede, explorando a transferência de streamings e processando decodificação de blocos. Como resultados, foi possível constatar que o Elastic-RAN pode atingir ganhos que vão de 4% a 26%, em relação aos custos de execução, quando comparado à abordagem de elasticidade tradicional. Além disso, obteve melhor eficiência para todos os perfis de carga e reduziu em até 55% a quantidade de operações elásticas necessárias. Outrossim, frente a abordagem sem elasticidade, os ganhos de custos foram ainda superiores, ficando entre 51% e 70%. / It is expected that, by 2020, cell phone networks will have been increased 10 times their coverage area, with more than 50 billion connected devices, supporting 100 times more user equipment and increasing data rate capacity by 1000 times. This will lead to a massive increase in data traffic, fostering the development of 5G and making industry and scientific initiatives turn their efforts to meet this demand. In this scenario, Cloud Radio Access Networks (C-RANs) based researches, an architecture that consolidates base stations (BSs) to a cloud-centric point, are gaining momentum, changing the idea of fixed and limited resources, as it benefits from one of the key features of Cloud Computing: resource elasticity. One of the major challenges in C-RAN architecture lies in the high complexity of orchestrating all of these computational resources in order to perform the requests processing with high performance and the lowest possible infrastructure cost. Considering this context, the present dissertation seeks to develop the Elastic-RAN model, proposing a multilevel non-blocking elasticity concept, with automatic orchestration of resources through the coordination of BBU Pools and their BBUs, with an adaptive elastic grain mechanism. The multilevel non-blocking elasticity allows it control the level of BBU Pool (physical machine), given the high volume of traffic and the suggested maximum distance between antennas and pools, and the level of BBU (virtual machine), due to the high CPU processing and memory required for the requests, so as not to penalize the current processing. The adaptive elastic grain mechanism allows the provisioning and mapping of resources on demand and at runtime, considering the current use of resources, so that each elastic action is performed with a grain close to the current processing needs. The Elastic-RAN model was evaluated through experiments that simulated different load profiles, which are executed in an intensive CPU and network traffic application, exploiting the transfer of streamings and processing block decoding. As a result, it was possible to observe that Elastic-RAN may achieve gains ranging from 4 % to 26 %, in relation to execution costs, when compared to the traditional elasticity approach. In addition, it achieved better efficiency for all load profiles and reduced by 55 % the amount of elastic operations required. Also, given the non-elasticity approach, cost gains were even higher, going from 51 % to 70 %.