Título:
End-to-end quality of service seen by applications : a statistical learning approach
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Autor:
Belzarena, Pablo
Aspirot, Laura
Aspirot, Laura
Tutor:
Tipo de documento:
Preprint
Editor:
Palabras clave:
End-to-end active measurements
Statistical learning
Nadaraya-Watson
Support Vector Machines
QoS
Statistical learning
Nadaraya-Watson
Support Vector Machines
QoS
Descriptores:
Telecomunicaciones
Año de publicación:
2010
Contenido:
Resumen:
The focus of this work is on the estimation of quality of servi ce (QoS) parameters seen by an application. Our proposal is based on end-to-end active measurements and sta tistical learning tools. We propose a methodology where the system is trained during short periods with application flows and probe packets bursts. We learn the relation be- tween QoS parameters seen by the application and the state of the network path, which is inferred from the interarrival times of the probe packets bursts. We obtain a continuous non intrusive QoS monitoring methodology. We propose two di ff erent estimators of the network state and analyze them using Nadaraya-Watson estimator and Support Vector Machines (SVM) for regression. We compare these approaches and we show results obtained by simulations and by measures in operational networks
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Citación:
Belzarena, P., Aspirot, L. End-to-end quality of service seen by applications : a statistical learning approach [Preprint] Publicado en Computer Networks, 2010, v. 54, no. 17. https://doi.org/10.1016/j.comnet.2010.06.004.
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Departamento académico:
Telecomunicaciones
Grupo de investigación:
Análisis de Redes, Tráfico y Estadísticas de Servicios
Licencia:
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| BA10.pdf | — | 938.62 KB | Adobe PDF |