Traffic generator using Perlin Noise
Fecha
2012Versión
Acceso abierto / Sarbide irekia
Tipo
Contribución a congreso / Biltzarrerako ekarpena
Impacto
|
10.1109/GLOCOM.2012.6503384
Resumen
Study 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 befor ...
[++]
Study 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. [--]
Materias
Perlin noise,
Traffic generator
Editor
IEEE
Publicado en
Global Communications Conference (GLOBECOM), 2012 IEEE
Notas
Trabajo presentado a IEEE Global Communications Conference, Globecom 2012; Optical Networks and Systems (ONS) Symposium, 3-7 de diciembre de 2012. Anaheim (Estados Unidos)
Departamento
Universidad Pública de Navarra. Departamento de Automática y Computación /
Nafarroako Unibertsitate Publikoa. Automatika eta Konputazioa Saila
Versión del editor
Entidades Financiadoras
This work was supported by the Spanish Ministry of Science and Innovation
through the research project INSTINCT (TEC-2010-21178-C02-01). Also, the
authors want to thank Spanish thematic network IPoTN (TEC2010-12250-E)
and Public University of Navarre for funding through PIF grant.