4 research outputs found

    Flexible Traffic Management in Broadband Access Networks using Software Defined Networking

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    Abstract-Over the years, the demand for high bandwidth services, such as live and on-demand video streaming, steadily increased. The adequate provisioning of such services is challenging and requires complex network management mechanisms to be implemented by Internet service providers (ISPs). In current broadband network architectures, the traffic of subscribers is tunneled through a single aggregation point, independent of the different service types it belongs to. While having a single aggregation point eases the management of subscribers for the ISP, it implies huge bandwidth requirements for the aggregation point and potentially high end-to-end latency for subscribers. An alternative would be a distributed subscriber management, adding more complexity to the management itself. In this paper, a new traffic management architecture is proposed that uses the concept of Software Defined Networking (SDN) to extend the existing Ethernet-based broadband network architecture, enabling a more efficient traffic management for an ISP. By using SDN-enabled home gateways, the ISP can configure traffic flows more dynamically, optimizing throughput in the network, especially for bandwidth-intensive services. Furthermore, a proofof-concept implementation of the approach is presented to show the general feasibility and study configuration tradeoffs. Analytic considerations and testbed measurements show that the approach scales well with an increasing number of subscriber sessions

    Comnet: Annual Report 2013

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    Mapeamento de qualidade de experiência (QOE) através de qualidade de serviço (QOS) focado em bases de dados distribuídas

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    Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2017.A falta de conceitualização congruente sobre qualidade de serviço (QoS) para bases de dados (BDs) foi o fator que impulsionou o estudo resultante nesta tese. A definição de QoS como uma simples verificação de se um nó corre risco de falha devido ao número de acessos, como faziam, na época do levantamento bibliométrico desta tese, alguns sistemas comerciais, era uma simplificação exagerada para englobar um conceito tão complexo. Outros trabalhos que dizem lidar com estes conceitos também não são exatos, em termos matemáticos, e não possuem definições concretas ou com qualidade passível de utilização ou replicação, o que torna inviável sua aplicação ou mesmo verificação. O foco deste estudo é direcionado à bases de dados distribuídas (BDDs), de maneira que a conceitualização aqui desenvolvida é também compatível, ao menos parcialmente, com modelos não distribuídos de BDs. As novas definições de QoS desenvolvidas são utilizadas para se lidar com o conceito correlacionado de qualidade de experiência (QoE), em uma abordagem em nível de sistema focada em completude de QoS. Mesmo sendo QoE um conceito multidimensional, difícil de ser mensurado, o foco é mantido em uma abordagem passível de mensuramento, de maneira a permitir que sistemas de BDDs possam lidar com autoavaliação. A proposta de autoavaliação surge da necessidade de identificação de problemas passíveis de autocorreção. Tendo-se QoS bem definida, de maneira estatística, pode-se fazer análise de comportamento e tendência comportamental de maneira a se inferir previsão de estados futuros, o que permite o início de processo de correção antes que se alcance estados inesperados, por predição estatística. Sendo o objetivo geral desta tese a definição de métricas de QoS e QoE, com foco em BDDs, lidando com a hipótese de que é possível se definir QoE estatisticamente com base em QoS, para propósitos de nível de sistema. Ambos os conceitos sendo novos para BDDs quando lidando com métricas mensuráveis exatas. E com estes conceitos então definidos, um modelo de recuperação arquitetural é apresentado e testado para demonstração de resultados quando da utilização das métricas definidas para predição comportamental.Abstract : The hitherto lack of quality of service (QoS) congruent conceptualization to databases (DBs) was the factor that drove the initial development of this thesis. To define QoS as a simple verification that if a node is at risk of failure due to memory over-commitment, as did some commercial systems at the time that was made the bibliometric survey of this thesis, it is an oversimplification to encompass such a complex concept. Other studies that quote to deal with this concept are not accurate and lack concrete definitions or quality allowing its use, making infeasible its application or even verification. Being the focus targeted to distributed databases (DDBs), the developed conceptualization is also compatible, at least partially, with models of non-distributed DBs. These newfound QoS settings are then used to handle the correlated concept of quality of experience (QoE) in a system-level approach, focused on QoS completeness. Being QoE a multidimensional concept, hard to be measured, the focus is kept in an approach liable of measurement, in a way to allow DDBs systems to deal with self-evaluation. The idea of self-evaluation arises from the need of identifying problems subject to self-correction. With QoS statistically well-defined, it is possible to analyse behavior and to indetify tendencies in order to predict future states, allowing early correction before the system reaches unexpected states. Being the general objective of this thesis the definition of metrics of QoS and QoE, focused on DDBs, dealing with the hypothesis that it is possible to define QoE statistically based on QoS, for system level purposes. Both these concepts being new to DDBs when dealing with exact measurable metrics. Once defined these concepts, an architectural recovering model is presented and tested to demonstrate the results when using the metrics defined for behavioral prediction

    SMARTenIT cloud traffic management approach and architectural considerations

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    The Internet has seen a strong move to support new overlay applications offered over the cloud, which demand for a coherent and integrated control in underlying heterogeneous networks in a scalable, resilient, and costefficient manner. A tighter integration of network management and cloud service functionality can lead to cross-layer optimization of operations and management, thus, being a promising approach to offer a large business potential in operational perspectives for all players involved. In this paper the SmartenIT approach is presented, which targets at a cross-layer traffic management by providing incentives to the involved stakeholders, i.e., providers of cloud-based applications, network operators, cloud operators, and end-users, to ensure a QoE-awareness. SmartenIT designs and develops traffic management solutions and mechanisms to meet accordingly special application requirements and to address efficiently load and traffic patterns, exploiting also social information in terms of user relations, interests and behaviour patterns. Additionally, the energy efficiency with respect to both end-user devices and underlying networking and cloud service provisioning infrastructure is tackled to ensure an operationally efficient management. Furthermore, this paper describes three scenarios of major interest to SmartenIT and discusses the possible impact of the SmartenIT approach on metrics of interest associated to each involved stakeholder. Finally, a conceptual architectural framework is introduced and major design axes and describe key functionalities are described; this conceptual architecture constitutes the basis for the development of the SmartenIT architecture
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