3,130 research outputs found

    DeMMon Decentralized Management and Monitoring Framework

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    The centralized model proposed by the Cloud computing paradigm mismatches the decentralized nature of mobile and IoT applications, given the fact that most of the data production and consumption is performed by end-user devices outside of the Data Center (DC). As the number of these devices grows, and given the need to transport data to and from DCs for computation, application providers incur additional infrastructure costs, and end-users incur delays when performing operations. These reasons have led us into a post-cloud era, where a new computing paradigm arose: Edge Computing. Edge Computing takes into account the broad spectrum of devices residing outside of the DC, closer to the clients, as potential targets for computations, potentially reducing infrastructure costs, improving the quality of service (QoS) for end-users and allowing new interaction paradigms between users and applications. Managing and monitoring the execution of these devices raises new challenges previously unaddressed by Cloud computing, given the scale of these systems and the devices’ (potentially) unreliable data connections and heterogenous computational power. The study of the state-of-the-art has revealed that existing resource monitoring and management solutions require manual configuration and have centralized components, which we believe do not scale for larger-scale systems. In this work, we address these limitations by presenting a novel Decentralized Management and Monitoring (“DeMMon”) system, targeted for edge settings. DeMMon provides primitives to ease the development of tools that manage computational resources that support edge-enabled applications, decomposed in components, through decentralized actions, taking advantage of partial knowledge of the system. Our solution was evaluated to amount to its benefits regarding information dissemination and monitoring capabilities across a set of realistic emulated scenarios of up to 750 nodes with variable failure rates. The results show the validity of our approach and that it can outperform state-of-the-art solutions regarding scalability and reliabilityO modelo centralizado de computação utilizado no paradigma da Computação na Nuvem apresenta limitações no contexto de aplicações no domínio da Internet das Coisas e aplicações móveis. Neste tipo de aplicações, os dados são produzidos e consumidos maioritariamente por dispositivos que se encontram na periferia da rede. Desta forma, transportar estes dados de e para os centros de dados impõe uma carga excessiva nas infraestruturas de rede que ligam os dispositivos aos centros de dados, aumentando a latência de respostas e diminuindo a qualidade de serviço para os utilizadores. Para combater estas limitações, surgiu o paradigma da Computação na Periferia, este paradigma propõe a execução de computações, e potencialmente armazenamento de dados, em dispositivos fora dos centros de dados, mais perto dos clientes, reduzindo custos e criando um novo leque de possibilidades para efetuar computações distribuídas mais próximas dos dispositivos que produzem e consomem os dados. Contudo, gerir e supervisionar a execução desses dispositivos levanta obstáculos não equacionados pela Computação na Nuvem, como a escala destes sistemas, ou a variabilidade na conectividade e na capacidade de computação dos dispositivos que os compõem. O estudo da literatura revela que ferramentas populares para gerir e supervisionar aplicações e dispositivos possuem limitações para a sua escalabilidade, como por exemplo, pontos de falha centralizados, ou requerem a configuração manual de cada dispositivo. Nesta dissertação, propõem-se uma nova solução de monitorização e disseminação de informação descentralizada. Esta solução oferece operações que permitem recolher informação sobre o estado do sistema, de modo a ser utilizada por soluções (também descentralizadas) que gerem aplicações especializadas para executar na periferia da rede. A nossa solução foi avaliada em redes emuladas de várias dimensões com um máximo de 750 nós, no contexto de disseminação e de monitorização de informação. Os nossos resultados mostram que o nosso sistema consegue ser mais robusto ao mesmo tempo que é mais escalável quando comparado com o estado da arte

    A Survey on the Contributions of Software-Defined Networking to Traffic Engineering

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    Since the appearance of OpenFlow back in 2008, software-defined networking (SDN) has gained momentum. Although there are some discrepancies between the standards developing organizations working with SDN about what SDN is and how it is defined, they all outline traffic engineering (TE) as a key application. One of the most common objectives of TE is the congestion minimization, where techniques such as traffic splitting among multiple paths or advanced reservation systems are used. In such a scenario, this manuscript surveys the role of a comprehensive list of SDN protocols in TE solutions, in order to assess how these protocols can benefit TE. The SDN protocols have been categorized using the SDN architecture proposed by the open networking foundation, which differentiates among data-controller plane interfaces, application-controller plane interfaces, and management interfaces, in order to state how the interface type in which they operate influences TE. In addition, the impact of the SDN protocols on TE has been evaluated by comparing them with the path computation element (PCE)-based architecture. The PCE-based architecture has been selected to measure the impact of SDN on TE because it is the most novel TE architecture until the date, and because it already defines a set of metrics to measure the performance of TE solutions. We conclude that using the three types of interfaces simultaneously will result in more powerful and enhanced TE solutions, since they benefit TE in complementary ways.European Commission through the Horizon 2020 Research and Innovation Programme (GN4) under Grant 691567 Spanish Ministry of Economy and Competitiveness under the Secure Deployment of Services Over SDN and NFV-based Networks Project S&NSEC under Grant TEC2013-47960-C4-3-

    Segment Routing: a Comprehensive Survey of Research Activities, Standardization Efforts and Implementation Results

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    Fixed and mobile telecom operators, enterprise network operators and cloud providers strive to face the challenging demands coming from the evolution of IP networks (e.g. huge bandwidth requirements, integration of billions of devices and millions of services in the cloud). Proposed in the early 2010s, Segment Routing (SR) architecture helps face these challenging demands, and it is currently being adopted and deployed. SR architecture is based on the concept of source routing and has interesting scalability properties, as it dramatically reduces the amount of state information to be configured in the core nodes to support complex services. SR architecture was first implemented with the MPLS dataplane and then, quite recently, with the IPv6 dataplane (SRv6). IPv6 SR architecture (SRv6) has been extended from the simple steering of packets across nodes to a general network programming approach, making it very suitable for use cases such as Service Function Chaining and Network Function Virtualization. In this paper we present a tutorial and a comprehensive survey on SR technology, analyzing standardization efforts, patents, research activities and implementation results. We start with an introduction on the motivations for Segment Routing and an overview of its evolution and standardization. Then, we provide a tutorial on Segment Routing technology, with a focus on the novel SRv6 solution. We discuss the standardization efforts and the patents providing details on the most important documents and mentioning other ongoing activities. We then thoroughly analyze research activities according to a taxonomy. We have identified 8 main categories during our analysis of the current state of play: Monitoring, Traffic Engineering, Failure Recovery, Centrally Controlled Architectures, Path Encoding, Network Programming, Performance Evaluation and Miscellaneous...Comment: SUBMITTED TO IEEE COMMUNICATIONS SURVEYS & TUTORIAL

    Cost-Aware Resource Management for Decentralized Internet Services

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    Decentralized network services, such as naming systems, content distribution networks, and publish-subscribe systems, play an increasingly critical role and are required to provide high performance, low latency service, achieve high availability in the presence of network and node failures, and handle a large volume of users. Judicious utilization of expensive system resources, such as memory space, network bandwidth, and number of machines, is fundamental to achieving the above properties. Yet, current network services typically rely on less-informed, heuristic-based techniques to manage scarce resources, and often fall short of expectations. This thesis presents a principled approach for building high performance, robust, and scalable network services. The key contribution of this thesis is to show that resolving the fundamental cost-benefit tradeoff between resource consumption and performance through mathematical optimization is practical in large-scale distributed systems, and enables decentralized network services to meet efficiently system-wide performance goals. This thesis presents a practical approach for resource management in three stages: analytically model the cost-benefit tradeoff as a constrained optimization problem, determine a near-optimal resource allocation strategy on the fly, and enforce the derived strategy through light-weight, decentralized mechanisms. It builds on self-organizing structured overlays, which provide failure resilience and scalability, and complements them with stronger performance guarantees and robustness under sudden changes in workload. This work enables applications to meet system-wide performance targets, such as low average response times, high cache hit rates, and small update dissemination times with low resource consumption. Alternatively, applications can make the maximum use of available resources, such as storage and bandwidth, and derive large gains in performance. I have implemented an extensible framework called Honeycomb to perform cost-aware resource management on structured overlays based on the above approach and built three critical network services using it. These services consist of a new name system for the Internet called CoDoNS that distributes data associated with domain names, an open-access content distribution network called CobWeb that caches web content for faster access by users, and an online information monitoring system called Corona that notifies users about changes to web pages. Simulations and performance measurements from a planetary-scale deployment show that these services provide unprecedented performance improvement over the current state of the art

    Privacy-Friendly Collaboration for Cyber Threat Mitigation

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    Sharing of security data across organizational boundaries has often been advocated as a promising way to enhance cyber threat mitigation. However, collaborative security faces a number of important challenges, including privacy, trust, and liability concerns with the potential disclosure of sensitive data. In this paper, we focus on data sharing for predictive blacklisting, i.e., forecasting attack sources based on past attack information. We propose a novel privacy-enhanced data sharing approach in which organizations estimate collaboration benefits without disclosing their datasets, organize into coalitions of allied organizations, and securely share data within these coalitions. We study how different partner selection strategies affect prediction accuracy by experimenting on a real-world dataset of 2 billion IP addresses and observe up to a 105% prediction improvement.Comment: This paper has been withdrawn as it has been superseded by arXiv:1502.0533

    Software Defined Networking:Applicability and Service Possibilities

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