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Computación y Sistemas
On-line version ISSN 2007-9737Print version ISSN 1405-5546
Comp. y Sist. vol.8 n.3 Ciudad de México Jan./Mar. 2005
Neuroplanificador de ATM Inalámbrico para Predecir y Conformar los Tráficos VBR y ABR
Neural Network Based Wireless ATM Scheduler for Predicting and Shaping VBR and ABR Traffics
Omar Castañeda Trujillo 1 y Carlos Felipe García Hernández2
1 Centro Nacional de Investigación y Desarrollo Tecnológico CENIDET Interior Internado Palmira S/N, Col. Palmira, Cuernavaca, Morelos México. 62490, Tel: (777) 3187741 Fax: (777) 3122434 email: omarcastanedat@yahoo.com
2 Instituto de Investigaciones Eléctricas IIE Calle Reforma No. 113, Col. Palmira, Cuernavaca, Morelos, México. 62490, Tel: (777) 3623811 Fax: (777) 3189854 emails: cfgarcia@iie.org.mx ; http://www.iie.org.mx/gci/curri30.htm
Artículo recibido en noviembre 25, 2002
Aceptado en octubre 25, 2004
Resumen
El manejo de los recursos de ancho de banda en un sistema WATM se vuelve más crítico que en ATM, debido a la escasez de estos y a lo menos confiable que es el medio de transmisión. Por lo tanto, se requieren mecanismos de control de tráfico y congestión más seguros que los usados en ATM. Este trabajo de investigación está dedicado al desarrollo de un planificador (Scheduler) de ATM Inalámbrico basado en la predicción de tráfico, usando redes neuronales artificiales, a la entrada de un Switch ATM para controlar y conformar el tráfico en la conexión de salida (enlace inalámbrico) del mismo Switch y con ello disminuir las condiciones de congestionamiento provocadas principalmente por el tráfico en forma de ráfagas de los servicios ABR y VBR de tiempo real y de tiempo no real. Se han considerado los mecanismos de Control de Admisión de Conexiones, el Control de Flujo ABR y la aplicación de retardos de celda para el manejo de la ocupación del buffer de la cola de salida del Switch; controlando y conformando el tráfico de salida, reduciendo las condiciones de congestionamiento y mejorándose la distribución de utilización de ancho de banda del enlace inalámbrico entre los servicios VBR y ABR.
Palabras clave: ATM, inalámbrico, WATM, planificador, red neuronal artificial, neuroplanificador, predicción de tráfico, conformación de tráfico, tráfico de tiempo real, VBR, ABR, control de flujo, control de tráfico, control de congestión, CAC, control de admisión de conexiones, Hydragyrum, simulación, calidad de servicio, QoS y ocupación del buffer.
Abstract
Managing of the bandwidth resources in a WATM system, it results more critical than in an ATM system, due to the resources scarcity and to the transmission medium with lesser reliability. Therefore, traffic and congestion control mechanisms, more secure than the ones used in ATM, are required. This research work is aimed at the development of a wireless ATM scheduler based on the traffic prediction, using artificial neural networks at the ATM switch entrance, in order to control and shape the traffic in the switch exit connection (wireless link). Consequently, this reduces the congestion conditions mainly originated for the bursty traffic from the real time and nonreal time ABR and VBR services. Connection Admission Control and ABR Flow Control mechanisms and applying delays in cells to manage the switch exit queue's buffer occupancy, have been considered, in order to control and shape the output traffic, reducing the congestion conditions and improving the wirelesslink bandwidth utilization distribution between the VBR and ABR services.
Keywords: ATM, wireless, WATM, scheduler, artificial neural network, neuroscheduler, traffic prediction, traffic shaping, real time traffic, VBR, ABR, flow control, traffic control, congestion control, CAC, connection admission control, Hydragyrum, simulation, quality of service, QoS and buffer occupancy.
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