Person: Prieto Suárez, Iria
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Prieto Suárez
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Iria
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Automática y Computación
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7276
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Publication Open Access Traffic generator using Perlin Noise(IEEE, 2012) Prieto Suárez, Iria; Izal Azcárate, Mikel; Morató Osés, Daniel; Magaña Lizarrondo, Eduardo; Automática y Computación; Automatika eta Konputazioa; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaStudy of high speed networks such as optical next generation burst or packet switched networks require large amounts of synthetic traffic to feed simulators. Methods to generate self-similar long range dependent traffic already exist but they usually work by generating large blocks of traffic of fixed time duration. This limits simulated time or require very high amount of data to be stored before simulation. On this work it is shown how self-similar traffic can be generated using Perlin Noise, an algorithm commonly used to generate 2D/3D noise for natural looking graphics. 1-dimension Perlin Noise can be interpreted as network traffic and used to generate long range dependent traffic for network simulation. The algorithm is compared to more classical approach Random Midpoint Displacement showing at traffic generated is similar but can be generated continuously with no fixed block size.Publication Open Access TNS research in progress(Universidad Politécnica de Cartagena, Servicio de Documentación, 2012) Izal Azcárate, Mikel; Prieto Suárez, Iria; Espina Antolín, Félix; Morató Osés, Daniel; Magaña Lizarrondo, Eduardo; Automática y Computación; Automatika eta Konputazioa; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaThis paper summarizes latest works of Telematic, Networks and Services research group (TNS) of Public University of Navarra in the topics of FIERRO thematic network. Last two papers sent to major conferences are addressed First work shows how self-similar traffic can be generated using Perlin Noise, an algorithm commonly used to generate 2D/3D noise for natural looking graphics. 1-dimension Perlin Noise can be interpreted as network traffic and used to generate long range dependent traffic for network simulation. The algorithm is compared to more classical approach Random Midpoint Displacement showing at traffic generated is similar but can be generated continuously with no fixed block size. Second work presents two novel cloning schemes for video delivery in OBS networks that dramatically improve user perceived content quality. These schemes take into account the special characteristics of compressed video traffic. Analytical and simulation results show up to 40% QoE improvement without a substantial increase in the overall network traffic and without increasing the number of bursts in the network. The results show the strong dependency of this novel cloning scheme on the video traffic structure due to the coding mechanisms.