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ABR traffic management using minimal resource allocation (neural) networks

✍ Scribed by N. Hock Soon; N. Sundararajan; P. Saratchandran

Book ID: 104273779
Publisher: Elsevier Science
Year: 2002
Tongue: English
Weight: 428 KB
Volume: 25
Category: Article
ISSN: 0140-3664
DOI: 10.1016/s0140-3664(01)00331-0

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✦ Synopsis

This paper presents an adaptive available bit rate (ABR) traf®c management scheme in asynchronous transfer mode (ATM) networks using the newly developed minimal resource allocation network (MRAN). MRAN generates a minimal radial basis function (RBF) neural network by adding and pruning the hidden neurons based on the input data and is well suited for on-line adaptive control of time varying nonlinear systems. In this paper, the ATM traf®c is modeled using the network simulation package OPNET. The performance of MRAN-controller is compared with the conventional ABR control scheme explicit rate indication with congestion avoidance (ERICA) for different traf®c scenarios such as bursty and Variable Bit Rate (VBR) traf®c. Results indicate that MRAN-controller performs better than ERICA by keeping the queue length and delay to a minimum while maintaining a higher link utilization and throughput.

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