A neural network approach towards adaptive congestion control in broadband ATM networks

Author

Chen, Xiaoqiang ; Leslie, Ian M.

Author_Institution

Comput. Lab., Cambridge Univ., UK

fYear

1991

fDate

2-5 Dec 1991

Firstpage

115

Abstract

The authors present an adaptive control scheme based on neural networks to solve a general quality-of-service (QOS) control problem in broadband ATM (asynchronous transfer mode) networks. The control algorithms developed for training neural networks are a direct application of the error backpropagation learning method with those modifications required to pose the problem in a QOS control framework. To illustrate the present scheme´s ability to control, examples of dynamic models are studied through simulations

Keywords

adaptive control; broadband networks; learning systems; neural nets; telecommunications control; time division multiplexing; adaptive congestion control; asynchronous transfer mode; broadband ATM networks; error backpropagation learning method; neural networks; quality-of-service; Adaptive control; Adaptive systems; Communication system traffic control; Computer networks; Intelligent networks; Loss measurement; Neural networks; Power system modeling; Programmable control; Traffic control;

fLanguage

English

Publisher

ieee

Conference_Titel

Global Telecommunications Conference, 1991. GLOBECOM '91. 'Countdown to the New Millennium. Featuring a Mini-Theme on: Personal Communications Services

Conference_Location

Phoenix, AZ

Print_ISBN

0-87942-697-7

Type

conf

DOI

10.1109/GLOCOM.1991.188367

Filename

188367