121 research outputs found

    Contribution à l'amélioration de l'efficacité des réseaux IP sur WDM en évaluant et en dépassant les limites du dimensionnement multicouche

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    The traffic passing through core networks grows by nearly 25% each year. To bring the costs under control, the different network layers of the network should work together to include more and more parameters during the network planning phase. This is called “multilayer network planning”. We study the multilayer network planning of static networks composed of two circuit switched layers (typically IP-over-WDM). We propose a semi-analytical model explaining the behavior of algorithms responsible for aggregation and routing in both layers. This theory allows comparing multilayer planning algorithms between them, but also explaining and enhancing their efficiency. We then describe the impact of the optical reach constraint in WDM networks on the results of a multilayer planning algorithm. Finally, we explain how these results apply to the design of future networks (dynamic and with heterogeneous optical layers)La quantité de données devant être transportée via les réseaux de cœur croit de près de 25% par an. Pour maîtriser les coûts, les différentes couches du réseau doivent mettre des informations en commun pour inclure de plus en plus de paramètres lors du dimensionnement du réseau. Cela s’appelle « dimensionnement multicouche ». Nous étudions le dimensionnement multicouche de réseaux statiques composés de deux couches utilisant la commutation en mode circuit (typiquement IP-sur-WDM). Nous proposons un modèle semi-analytique expliquant le comportement des algorithmes responsables de l’agrégation et du routage dans les deux couches. Ce cadre théorique permet de comparer les algorithmes de dimensionnement multicouche entre eux, mais aussi d’expliquer et d’améliorer leur efficience. Nous décrivons ensuite comment la contrainte de portée optique affecte les résultats d’un algorithme de dimensionnement multicouche. Enfin, nous expliquons comment ces résultats s'appliquent au dimensionnement des réseaux de nouvelle génération (dynamiques et hétérogènes en capacité optique

    Evaluating the energy consumption and the energy savings potential in ICT backbone networks

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    Alocação de recursos em redes ópticas elásticas baseadas em multiplexação por divisão espacial

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    Orientador: Nelson Luis Saldanha da FonsecaDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Tecnologias de redes ópticas baseadas em fibras mono-núcleo e mono-modo possuem limite de capacidade e não conseguem suprir a demanda crescente de largura de banda. Um forma de resolver esse problema se dá através do uso de multiplexação por divisão espacial (SDM - \textit{Space-Division Multiplexing}). A transmissão de dados em SDM ocorre através de múltiplos núcleos agrupados em um único filamento de fibra, ou utilizando múltiplos modos transversais suportados por um núcleo. A combinação da flexibilidade de redes ópticas elásticas (EON - \textit{Elastic Optical Networks}) e a alta capacidade do SDM é promissora para o futuro das redes ópticas. Na camada de enlace, quando uma nova solicitação para estabelecimento de conexão chega, é necessário fazer a reserva de recursos para realizar essa conexão. A determinação dos recursos a serem alocados é dada pela solução do problema de roteamento, alocação de núcleo e \textit{slots} (RCSA - \textit{Routing, Core and Spectrum Allocation}). Na alocação de recursos, algumas restrições devem ser respeitadas, tais como a contiguidade e continuidade dos \textit{slots} de frequência, e tolerância ao \textit{crosstalk} espacial. Estas restrições implicam em uma maior complexidade para a acomodação do tráfego das conexões. A virtualização de redes permite que redes virtuais compartilhem recursos físicos, simplificando o gerenciamento de recursos na camada óptica, oferecendo flexibilidade na alocação de recursos e segurança dos serviços. Um dos principais desafios da virtualização é configurar de forma eficiente as redes virtuais, que consiste na alocação de recursos físicos para acomodá-las. Esta tese propõe soluções para o problema do RCSA em redes SDM-EON. A primeira contribuição desta tese é um algoritmo que considera o equilíbrio entre eficiência energética e bloqueio de requisições. Propõe-se um algoritmo de agregação de tráfego em lote, capitalizando na flexibilidade temporal para satisfazer requisições com o objetivo de formar lotes de requisições, aumentando assim a probabilidade de serem atendidas as requisições em um outro momento. A segunda contribuição desta tese é direcionada para a solução do problema da fragmentação, que ocorre em cenários onde pequenos conjuntos de \textit{slots} disponíveis ficam espalhados no espectro, causando o bloqueio de novas requisição. Propõem-se um conjunto de algoritmos proativos e reativos. Os algoritmos proativos utilizam diferentes técnicas, tais como, múltiplos caminhos, priorização de núcleo e área, bem como métricas de avaliação da fragmentação na composição de caminhos. O algoritmo reativo utiliza aprendizagem de máquina para fazer um rearranjo espectral e aumentar a capacidade de prevenção da fragmentação no RCSA. A terceira contribuição desta tese é uma solução para aumentar a eficiência do compartilhamento de recursos em redes virtuais. Este problema consiste na configuração de enlaces e nós virtuais para caminhos e nós físicos, respectivamente. A solução proposta introduz uma arquitetura utilizando aprendizado de máquina, que age como um assistente no processo de configuração de redes virtuaisAbstract: Optical network technologies based on a single-core and single-mode fibers have a limited capacity and cannot provide enough resources to a constant increase of bandwidth demands. One approach to overcome this is the use of Space-Division Multiplexing (SDM) which relies on sending data through multiple cores embedded into a single strand of fiber or using multiple transverse modes supported by a core. The combination of the flexibility of Elastic Optical Networks (EONs) and the high capacity of SDM is a promising solution to cope with the bandwidth demands. At the network level, when a traffic request arrives, it needs to reserve network resources to establish it. One approach to accommodate traffic demand over optical networks is the Routing, Core and Spectrum Allocation (RCSA), in which end-to-end lightpaths are offered for each individual request. In these scenarios, during the allocation process, some constraints need to be respected, such as contiguity and continuity of slots (selected in the resource selection process), and spatial crosstalk. These constraints pose extra complexity to accommodate the requests for the lightpath establishment. As one of the possible solutions, network virtualization is capable of improving the efficiency of optical networks, by allowing virtual networks to share the resources of physical networks, simplifying the management of resource and providing flexibility in resource allocation. One of the main challenges of network virtualization is to configure a virtual network efficiently which comprises allocating physical resources to accommodate incoming virtual networks. This thesis proposes solutions to the RCSA problem and the virtual network configuration problem for SDM-EON networks. The first contribution of this thesis is an algorithm to promote an equilibrium between reduction of the network energy consumption and reduction of the blocking of requests. For this purpose, we introduce a traffic grooming algorithm using batches, which takes advantage of the deadline of each request to form batches, increasing the chances of the requests to be established at another time. The second contribution of this thesis is a set of algorithms using different techniques to handle the fragmentation problem, where a small portion of available slot sequences end up scattered in a fiber link, blocking future requests, called the fragmentation problem. For this purpose, we propose proactive and reactive algorithms. Proactive algorithms use different techniques, such as multipath routing, core, and area prioritization, and metrics to use in the route selection process. The reactive algorithm uses machine learning to rearrange the spectrum and tune the RCSA algorithm to prevent the fragmentation. The third contribution of this thesis proposes a solution to improve resource sharing in network virtualization. This problem consists in configuring virtual links and nodes to physical nodes and paths. For this purpose, we propose a learning assistant control loop to handle the virtual network configuration problemMestradoCiência da ComputaçãoMestra em Ciência da Computação131025/2017-1CNP

    Optimizing total cost of ownership (TCO) for 5G multi-tenant mobile backhaul (MBH) optical transport networks

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    Legacy network elements are reaching end-of-life and packet-based transport networks are not efficiently optimized. In particular, high density cell architecture in future 5G networks will face big technical and financial challenges due to avalanche of traffic volume and massive growth in connected devices. Raising density and ever-increasing traffic demand within future 5G Heterogeneous Networks (HetNets) will result in huge deployment, expansion and operating costs for upcoming Mobile BackHaul (MBH) networks with flat revenue generation. Thus, the goal of this dissertation is to provide an efficient physical network planning mechanism and an optimized resource engineering tool in order to reduce the Total Cost of Ownership (TCO) and increase the generated revenues. This will help Service Providers (SPs) and Mobile Network Operators (MNOs) to improve their network scalability and maintain positive Project Profit Margins (PPM). In order to meet this goal, three key issues are required to be addressed in our framework and are summarized as follows: i) how to design and migrate to a scalable and reliable MBH network in an optimal cost?, ii) how to control the deployment and activation of the network resources in such MBH based on required traffic demand in an efficient and cost-effective way?, and iii) how to enhance the resource sharing in such network and maximize the profit margins in an efficient way? As part of our contributions to address the first issue highlighted above and to plan the MBH with reduced network TCO and improved scalability, we propose a comprehensive migration plan towards an End-to-End Integrated-Optical-Packet-Network (E2-IOPN) for SP optical transport networks. We review various empirical challenges faced by a real SP during the transformation process towards E2-IOPN as well as the implementation of an as-built plan and a high-level design (HLD) for migrating towards lower cost-per-bit GPON, MPLS-TP, OTN and next-generation DWDM technologies. Then, we propose a longer-term strategy based on SDN and NFV approach that will offer rapid end-to-end service provisioning with costefficient centralized network control. We define CapEx and OpEx cost models and drive a cost comparative study that shows the benefit and financial impact of introducing new low-cost packet-based technologies to carry traffic from legacy and new services. To address the second issue, we first introduce an algorithm based on a stochastic geometry model (Voronoi Tessellation) to more precisely define MBH zones within a geographical area and more accurately calculate required traffic demands and related MBH infrastructure. In order to optimize the deployment and activation of the network resources in the MBH in an efficient and cost-effective way, we propose a novel method called BackHauling-as-a-Service (BHaaS) for network planning and Total Cost of Ownership (TCO) analysis based on required traffic demand and a "You-pay-only-for-what-you-use" approach. Furthermore, we enhance BHaaS performance by introducing a more service-aware method called Traffic-Profile-asa- Service (TPaaS) to further drive down the costs based on yearly activated traffic profiles. Results show that BHaaS and TPaaS may enhance by 22% the project benefit compared to traditional TCO model. Finally, we introduce a new cost (CapEx and OpEx) models for 5G multi-tenant Virtualized MBH (V-MBH) as part of our contribution to address the third issue. In fact, in order to enhance the resource sharing and maximize the network profits, we drive a novel pay-as-yougrow and optimization model for the V-MBH called Virtual-Backhaul-as-a-Service (VBaaS). VBaaS can serve as a planning tool to optimize the Project Profit Margin (PPM) while considering the TCO and the yearly generated Return-on-Investment (ROI). We formulate an MNO Pricing Game (MPG) for TCO optimization to calculate the optimal Pareto-Equilibrium pricing strategy for offered Tenant Service Instances (TSI). Then, we compare CapEx, OpEx, TCO, ROI and PPM for a specific use-case known in the industry as CORD project using Traditional MBH (T-MBH) versus Virtualized MBH (V-MBH) as well as using randomized versus Pareto-Equilibrium pricing strategies. The results of our framework offer SPs and MNOs a more precise estimation of traffic demand, an optimized infrastructure planning and yearly resource deployment as well as an optimized TCO analysis (CapEx and OpEx) with enhanced pricing strategy and generated ROI. Numerical results show more than three times increase in network profitability using our proposed solutions compared with Traditional MBH (T-MBH) methods

    Design and optimization of optical grids and clouds

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    Telecommunications Networks

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    This book guides readers through the basics of rapidly emerging networks to more advanced concepts and future expectations of Telecommunications Networks. It identifies and examines the most pressing research issues in Telecommunications and it contains chapters written by leading researchers, academics and industry professionals. Telecommunications Networks - Current Status and Future Trends covers surveys of recent publications that investigate key areas of interest such as: IMS, eTOM, 3G/4G, optimization problems, modeling, simulation, quality of service, etc. This book, that is suitable for both PhD and master students, is organized into six sections: New Generation Networks, Quality of Services, Sensor Networks, Telecommunications, Traffic Engineering and Routing

    Energy efficiency in content delivery networks

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    The increasing popularity of bandwidth-intensive video Internet services has positioned Content Distribution Networks (CDNs) in the limelight as the emerging provider platforms for video delivery. The goal of CDNs is to maximise the availability of content in the network while maintaining the quality of experience expected by users. This is a challenging task due to the scattered nature of video content sources and destinations. Furthermore, the high energy consumption associated with content distribution calls for developing energy-efficient solutions able to cater for the future Internet. This thesis addresses the problem of content placement and update while considering energy consumption in CDNs. First, this work contributed a new energy-efficient caching scheme that stores the most popular content at the edge of the core network and optimises the size of cached content to minimise energy usage. It takes into account the trend of daily traffic and recommends putting inactive segments of caches in sleep-mode during off-peak hours. Our results showed that power minimisation is achieved by deploying switch-off capable caches, and the trend of active cache segments over the time of day follows the trend of traffic. Second, the study explores different content popularity distributions and determines their influence on power consumption. The distribution of content popularity dictates the resultant cache hit ratio achieved by storing a certain number of videos. Therefore, it directly influences the power consumption of the cache. The evaluation results indicated that under video services where the popularity of content is very diverse, the optimum solution is to store the few most popular videos in caches. In contrast, when video popularities are similar, the most power efficient scheme is either to cache the whole library or to avoid caching completely depending on the size of the video library. Third, this thesis contributed an evaluation of the power consumption of the network under real world TV data and considering standard and high definition TV programmes. We proposed a cache replacement algorithm based on the predictable nature of TV viewings. The time-driven proactive cache replacement algorithm replaces cache contents several times a day to minimise power consumption. The algorithm achieves major power savings on top of the power reductions introduced by caching. CDNs are expected to continue to be the backbone for Internet video applications. This work has shown that storing the right amount of popular videos in core caches reduces from 42% to 72% of network power consumption considering a range of content popularity distributions. Maintaining up-to-date cache contents reduces up to 48% and 86% of power consumption considering fixed and sleep-mode capable caches, respectively. Reducing the energy consumption of CDNs provides a valuable contribution for future green video delivery

    Conserve and Protect Resources in Software-Defined Networking via the Traffic Engineering Approach

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    Software Defined Networking (SDN) is revolutionizing the architecture and operation of computer networks and promises a more agile and cost-efficient network management. SDN centralizes the network control logic and separates the control plane from the data plane, thus enabling flexible management of networks. A network based on SDN consists of a data plane and a control plane. To assist management of devices and data flows, a network also has an independent monitoring plane. These coexisting network planes have various types of resources, such as bandwidth utilized to transmit monitoring data, energy spent to power data forwarding devices and computational resources to control a network. Unwise management, even abusive utilization of these resources lead to the degradation of the network performance and increase the Operating Expenditure (Opex) of the network owner. Conserving and protecting limited network resources is thus among the key requirements for efficient networking. However, the heterogeneity of the network hardware and network traffic workloads expands the configuration space of SDN, making it a challenging task to operate a network efficiently. Furthermore, the existing approaches usually lack the capability to automatically adapt network configurations to handle network dynamics and diverse optimization requirements. Addtionally, a centralized SDN controller has to run in a protected environment against certain attacks. This thesis builds upon the centralized management capability of SDN, and uses cross-layer network optimizations to perform joint traffic engineering, e.g., routing, hardware and software configurations. The overall goal is to overcome the management complexities in conserving and protecting resources in multiple functional planes in SDN when facing network heterogeneities and system dynamics. This thesis presents four contributions: (1) resource-efficient network monitoring, (2) resource-efficient data forwarding, (3) using self-adaptive algorithms to improve network resource efficiency, and (4) mitigating abusive usage of resources for network controlling. The first contribution of this thesis is a resource-efficient network monitoring solution. In this thesis, we consider one specific type of virtual network management function: flow packet inspection. This type of the network monitoring application requires to duplicate packets of target flows and send them to packet monitors for in-depth analysis. To avoid the competition for resources between the original data and duplicated data, the network operators can transmit the data flows through physically (e.g., different communication mediums) or virtually (e.g., distinguished network slices) separated channels having different resource consumption properties. We propose the REMO solution, namely Resource Efficient distributed Monitoring, to reduce the overall network resource consumption incurred by both types of data, via jointly considering the locations of the packet monitors, the selection of devices forking the data packets, and flow path scheduling strategies. In the second contribution of this thesis, we investigate the resource efficiency problem in hybrid, server-centric data center networks equipped with both traditional wired connections (e.g., InfiniBand or Ethernet) and advanced high-data-rate wireless links (e.g., directional 60GHz wireless technology). The configuration space of hybrid SDN equipped with both wired and wireless communication technologies is massively large due to the complexity brought by the device heterogeneity. To tackle this problem, we present the ECAS framework to reduce the power consumption and maintain the network performance. The approaches based on the optimization models and heuristic algorithms are considered as the traditional way to reduce the operation and facility resource consumption in SDN. These approaches are either difficult to directly solve or specific for a particular problem space. As the third contribution of this thesis, we investigates the approach of using Deep Reinforcement Learning (DRL) to improve the adaptivity of the management modules for network resource and data flow scheduling. The goal of the DRL agent in the SDN network is to reduce the power consumption of SDN networks without severely degrading the network performance. The fourth contribution of this thesis is a protection mechanism based upon flow rate limiting to mitigate abusive usage of the SDN control plane resource. Due to the centralized architecture of SDN and its handling mechanism for new data flows, the network controller can be the failure point due to the crafted cyber-attacks, especially the Control-Plane- Saturation (CPS) attack. We proposes an In-Network Flow mAnagement Scheme (INFAS) to effectively reduce the generation of malicious control packets depending on the parameters configured for the proposed mitigation algorithm. In summary, the contributions of this thesis address various unique challenges to construct resource-efficient and secure SDN. This is achieved by designing and implementing novel and intelligent models and algorithms to configure networks and perform network traffic engineering, in the protected centralized network controller
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