IEICE TRANSACTIONS on Communications
A Trial Multilayer Perceptron Neural Network for ATM Connection Admission Control
Summary :
Future broadband ATM networks are expected to accommodate various kinds of multi-media services with different traffic characteristics and quality of service (QOS) requirements. However, it is very difficult to control traffic by conventional mechanisms in this complex traffic environment. As an alternative approach, a multilayer perceptron neural network model is proposed as an intelligent control mechanism like "a traffic control policeman" in order to perform ATM connection admission control. This proposed neural control model is analyzed by computer simulations in a homogeneous and heterogeneous traffic environment and the result shows the effectiveness of this intelligent control mechanism, compared with that of an analytical method.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E76-B No.3 pp.258-262
- Publication Date
- 1993/03/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section PAPER (Special Issue on Broadband ISDN --Application, Networking and Management--)
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Sang Hyuk KANG, Dan Keun SUNG, "A Trial Multilayer Perceptron Neural Network for ATM Connection Admission Control" in IEICE TRANSACTIONS on Communications,
vol. E76-B, no. 3, pp. 258-262, March 1993, doi: .
Abstract: Future broadband ATM networks are expected to accommodate various kinds of multi-media services with different traffic characteristics and quality of service (QOS) requirements. However, it is very difficult to control traffic by conventional mechanisms in this complex traffic environment. As an alternative approach, a multilayer perceptron neural network model is proposed as an intelligent control mechanism like "a traffic control policeman" in order to perform ATM connection admission control. This proposed neural control model is analyzed by computer simulations in a homogeneous and heterogeneous traffic environment and the result shows the effectiveness of this intelligent control mechanism, compared with that of an analytical method.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e76-b_3_258/_p
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@ARTICLE{e76-b_3_258,
author={Sang Hyuk KANG, Dan Keun SUNG, },
journal={IEICE TRANSACTIONS on Communications},
title={A Trial Multilayer Perceptron Neural Network for ATM Connection Admission Control},
year={1993},
volume={E76-B},
number={3},
pages={258-262},
abstract={Future broadband ATM networks are expected to accommodate various kinds of multi-media services with different traffic characteristics and quality of service (QOS) requirements. However, it is very difficult to control traffic by conventional mechanisms in this complex traffic environment. As an alternative approach, a multilayer perceptron neural network model is proposed as an intelligent control mechanism like "a traffic control policeman" in order to perform ATM connection admission control. This proposed neural control model is analyzed by computer simulations in a homogeneous and heterogeneous traffic environment and the result shows the effectiveness of this intelligent control mechanism, compared with that of an analytical method.},
keywords={},
doi={},
ISSN={},
month={March},}
Copy
TY - JOUR
TI - A Trial Multilayer Perceptron Neural Network for ATM Connection Admission Control
T2 - IEICE TRANSACTIONS on Communications
SP - 258
EP - 262
AU - Sang Hyuk KANG
AU - Dan Keun SUNG
PY - 1993
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E76-B
IS - 3
JA - IEICE TRANSACTIONS on Communications
Y1 - March 1993
AB - Future broadband ATM networks are expected to accommodate various kinds of multi-media services with different traffic characteristics and quality of service (QOS) requirements. However, it is very difficult to control traffic by conventional mechanisms in this complex traffic environment. As an alternative approach, a multilayer perceptron neural network model is proposed as an intelligent control mechanism like "a traffic control policeman" in order to perform ATM connection admission control. This proposed neural control model is analyzed by computer simulations in a homogeneous and heterogeneous traffic environment and the result shows the effectiveness of this intelligent control mechanism, compared with that of an analytical method.
ER -
English
