Cell loss rate estimation based on neural network for call admission control in ATM networks

Author

Masugi, Masao

Author_Institution

NTT Multimedia Networks Labs., Tokyo, Japan

Volume

1

fYear

1997

fDate

8-12 Jun 1997

Firstpage

195

Abstract

This paper proposes a neural network based cell loss rate estimation method for the real time call admission control (CAC) in ATM networks. Cell loss rates data calculated by the non-parametric method were adapted to optimize the three layer perceptron. By adjusting the connection strength between neurons in the model, cell loss rates can be effectively derived from average cell rates and peak cell rates in the ATM networks. Evaluation results suggest that the proposed method is useful for high-speed ATM CAC in multimedia traffic environments

Keywords

asynchronous transfer mode; multilayer perceptrons; multimedia communication; telecommunication congestion control; telecommunication traffic; ATM networks; average cell rates; call admission control; cell loss rate estimation; connection strength; multimedia traffic; neural network; neurons; nonparametric method; peak cell rates; three layer perceptron optimisation; Asynchronous transfer mode; Bandwidth; Call admission control; Intelligent networks; Laboratories; Neural networks; Neurons; Optimization methods; Quality of service; Traffic control;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications, 1997. ICC '97 Montreal, Towards the Knowledge Millennium. 1997 IEEE International Conference on

Conference_Location

Montreal, Que.

Print_ISBN

0-7803-3925-8

Type

conf

DOI

10.1109/ICC.1997.605195

Filename

605195