26 research outputs found

    Modelos Matemáticos Basados en Consumos Computacionales para el Estudio de Rendimiento de Sondas de Análisis de Tráfico en Redes de Datos

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    196 p.La monitorización de tráfico es una operación crítica dentro de las tareas de gestión de red. Por ello, es necesario disponer de herramientas y equipos que analicen el tráfico de red y detecten posibles anomalías, fallos de configuración, ataques o intrusiones. Este trabajo de Tesis se centra en el estudio de equipos denominados sondas de análisis de tráfico que realizan labores de monitorización. Tras analizar la evolución de estos sistemas desde las primeras redes Gigabit Ethernet hasta las redes 5G actuales, la Tesis propone modelos analíticos dirigidos a medir el rendimiento de dichos dispositivos. Se presentan tres modelos basados en teoría de colas: en el primero, sobre un cola tándem con un único servidor activo, se formula un proceso de decisión de Markov que optimiza el throughput de una sonda de análisis; en el segundo, se analiza y se mide el rendimiento de un sistema de captura de paquetes mediante un modelo de cola con vacations; por último, el tercero plantea una red abierta de colas para tomar decisiones en el despliegue de funciones virtuales de red (VNFs) de un servicio de Misión Crítica sobre una red 5G. Cada modelo se resuelve con una técnica diferente y posteriormente se valida, bien sea comparando sus resultados con medidas experimentales de una sonda real o bien mediante simulación

    35th Symposium on Theoretical Aspects of Computer Science: STACS 2018, February 28-March 3, 2018, Caen, France

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    Treatment-Based Classi?cation in Residential Wireless Access Points

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    IEEE 802.11 wireless access points (APs) act as the central communication hub inside homes, connecting all networked devices to the Internet. Home users run a variety of network applications with diverse Quality-of-Service requirements (QoS) through their APs. However, wireless APs are often the bottleneck in residential networks as broadband connection speeds keep increasing. Because of the lack of QoS support and complicated configuration procedures in most off-the-shelf APs, users can experience QoS degradation with their wireless networks, especially when multiple applications are running concurrently. This dissertation presents CATNAP, Classification And Treatment iN an AP , to provide better QoS support for various applications over residential wireless networks, especially timely delivery for real-time applications and high throughput for download-based applications. CATNAP consists of three major components: supporting functions, classifiers, and treatment modules. The supporting functions collect necessary flow level statistics and feed it into the CATNAP classifiers. Then, the CATNAP classifiers categorize flows along three-dimensions: response-based/non-response-based, interactive/non-interactive, and greedy/non-greedy. Each CATNAP traffic category can be directly mapped to one of the following treatments: push/delay, limited advertised window size/drop, and reserve bandwidth. Based on the classification results, the CATNAP treatment module automatically applies the treatment policy to provide better QoS support. CATNAP is implemented with the NS network simulator, and evaluated against DropTail and Strict Priority Queue (SPQ) under various network and traffic conditions. In most simulation cases, CATNAP provides better QoS supports than DropTail: it lowers queuing delay for multimedia applications such as VoIP, games and video, fairly treats FTP flows with various round trip times, and is even functional when misbehaving UDP traffic is present. Unlike current QoS methods, CATNAP is a plug-and-play solution, automatically classifying and treating flows without any user configuration, or any modification to end hosts or applications

    Proactive measurement techniques for network monitoring in heterogeneous environments

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    Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Tecnología Electrónica y de las Comunicaciones, 201

    Automated Inference System for End-To-End Diagnosis of Network Performance Issues in Client-Terminal Devices

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    Traditional network diagnosis methods of Client-Terminal Device (CTD) problems tend to be laborintensive, time consuming, and contribute to increased customer dissatisfaction. In this paper, we propose an automated solution for rapidly diagnose the root causes of network performance issues in CTD. Based on a new intelligent inference technique, we create the Intelligent Automated Client Diagnostic (IACD) system, which only relies on collection of Transmission Control Protocol (TCP) packet traces. Using soft-margin Support Vector Machine (SVM) classifiers, the system (i) distinguishes link problems from client problems and (ii) identifies characteristics unique to the specific fault to report the root cause. The modular design of the system enables support for new access link and fault types. Experimental evaluation demonstrated the capability of the IACD system to distinguish between faulty and healthy links and to diagnose the client faults with 98% accuracy. The system can perform fault diagnosis independent of the user's specific TCP implementation, enabling diagnosis of diverse range of client devicesComment: arXiv admin note: substantial text overlap with arXiv:1207.356
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