Dynamic Path Assignment for Broadband Networks Based on Neural Computation

Akira CHUGO; Ichiro IIDA

Dynamic Path Assignment for Broadband Networks Based on Neural Computation

Akira CHUGO, Ichiro IIDA

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This paper describes the application of a neural network to the optimal routing problem in broadband multimedia networks, where the objective is to maximize network utilization while considering the performance required for each call. In a multimedia environment, the performance required for each call is different, and an optimal path must be found whenever a call arrives. A neural network is appropriate for the computation of an optimal path, as it provides real-time solutions to difficult optimization problems. We formulated optimal routing based on the Hop field neural network model, and evaluated the basic behavior of neural networks. This evaluation confirmed the validity of the neural network formulation, which has a small computation time even if there are many nodes. This characteristic is especially suitable for a large-scale system. In addition, we performed a computer simulation of the proposed routing scheme and compared it with conventional alternate routing schemes. The results show the benefit of neural networks for the routing problem, as our scheme always balances the network load and attains high network utilization.

Publication: IEICE TRANSACTIONS on Communications Vol.E75-B No.7 pp.634-641

Publication Date: 1992/07/25

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Type of Manuscript: Special Section PAPER (Special Section on Network Planning)

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Akira CHUGO, Ichiro IIDA, "Dynamic Path Assignment for Broadband Networks Based on Neural Computation" in IEICE TRANSACTIONS on Communications, vol. E75-B, no. 7, pp. 634-641, July 1992, doi: .
Abstract: This paper describes the application of a neural network to the optimal routing problem in broadband multimedia networks, where the objective is to maximize network utilization while considering the performance required for each call. In a multimedia environment, the performance required for each call is different, and an optimal path must be found whenever a call arrives. A neural network is appropriate for the computation of an optimal path, as it provides real-time solutions to difficult optimization problems. We formulated optimal routing based on the Hop field neural network model, and evaluated the basic behavior of neural networks. This evaluation confirmed the validity of the neural network formulation, which has a small computation time even if there are many nodes. This characteristic is especially suitable for a large-scale system. In addition, we performed a computer simulation of the proposed routing scheme and compared it with conventional alternate routing schemes. The results show the benefit of neural networks for the routing problem, as our scheme always balances the network load and attains high network utilization.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/e75-b_7_634/_p

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@ARTICLE{e75-b_7_634,
author={Akira CHUGO, Ichiro IIDA, },
journal={IEICE TRANSACTIONS on Communications},
title={Dynamic Path Assignment for Broadband Networks Based on Neural Computation},
year={1992},
volume={E75-B},
number={7},
pages={634-641},
abstract={This paper describes the application of a neural network to the optimal routing problem in broadband multimedia networks, where the objective is to maximize network utilization while considering the performance required for each call. In a multimedia environment, the performance required for each call is different, and an optimal path must be found whenever a call arrives. A neural network is appropriate for the computation of an optimal path, as it provides real-time solutions to difficult optimization problems. We formulated optimal routing based on the Hop field neural network model, and evaluated the basic behavior of neural networks. This evaluation confirmed the validity of the neural network formulation, which has a small computation time even if there are many nodes. This characteristic is especially suitable for a large-scale system. In addition, we performed a computer simulation of the proposed routing scheme and compared it with conventional alternate routing schemes. The results show the benefit of neural networks for the routing problem, as our scheme always balances the network load and attains high network utilization.},
keywords={},
doi={},
ISSN={},
month={July},}

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TY - JOUR
TI - Dynamic Path Assignment for Broadband Networks Based on Neural Computation
T2 - IEICE TRANSACTIONS on Communications
SP - 634
EP - 641
AU - Akira CHUGO
AU - Ichiro IIDA
PY - 1992
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E75-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 1992
AB - This paper describes the application of a neural network to the optimal routing problem in broadband multimedia networks, where the objective is to maximize network utilization while considering the performance required for each call. In a multimedia environment, the performance required for each call is different, and an optimal path must be found whenever a call arrives. A neural network is appropriate for the computation of an optimal path, as it provides real-time solutions to difficult optimization problems. We formulated optimal routing based on the Hop field neural network model, and evaluated the basic behavior of neural networks. This evaluation confirmed the validity of the neural network formulation, which has a small computation time even if there are many nodes. This characteristic is especially suitable for a large-scale system. In addition, we performed a computer simulation of the proposed routing scheme and compared it with conventional alternate routing schemes. The results show the benefit of neural networks for the routing problem, as our scheme always balances the network load and attains high network utilization.
ER -