A new neuro-fuzzy system for efficient ATM traffic control

Author

Custodio, Jorge J. ; Tascón, Manuel ; Merino, Manuel ; Dimitriadis, Yannis A.

Author_Institution

Dept. of Signal Theory, Valladolid Univ., Spain

Volume

2

fYear

1999

fDate

1999

Firstpage

964

Abstract

We present and apply the fuzzy adaptive system ART-based (FasArt) neuro-fuzzy system to the problems of connection admission control (CAC) and usage parameter control (UPC). FasArt provides the advantages of both a fuzzy logic system (simplicity and interpretability of fuzzy rules) and an ART-based neural network (fast, stable and incremental learning). An extensive experimental work in the Ptolemy simulation environment is presented, together with an analysis of system performance. Besides the general fine properties of FasArt, a superior performance was confirmed in comparison to other conventional, fuzzy or neural systems in the UPC problem, with respect to selectiveness, low response time and false alarm probability. On the other hand, performance in the CAC problem was satisfactory, as far as cell loss rate and link usage are concerned, especially when FasArt was employed as a function identification system

Keywords

asynchronous transfer mode; ART-neural network; ATM traffic control; FasArt; cell loss rate; connection admission control; fuzzy adaptive system; fuzzy neural networks; incremental learning; link usage; usage parameter control;

fLanguage

English

Publisher

iet

Conference_Titel

Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470)

Conference_Location

Edinburgh

ISSN

0537-9989

Print_ISBN

0-85296-721-7

Type

conf

DOI

10.1049/cp:19991237

Filename

818062