Application of Genetic Algorithms to VOD Network Topology Optimization

Yoshiaki TANAKA; Olivier BERLAGE

Application of Genetic Algorithms to VOD Network Topology Optimization

Yoshiaki TANAKA, Olivier BERLAGE

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In this paper, we point out an architecture optimization problem for networks delivering services such as Video-On-Demand or, more precisely, two intertwined problems, i.e., the storage allocation of the videos among the storage nodes of the network and the choice of the network topology. We present and investigate the properties of a genetic algorithm which can handle such problems. This algorithm, as well as a greedy heuristics and simulated annealing, are then used to derive solutions in function of link and node cost parameters in a 36-node network. The results show that genetic algorithms are an effective class of algorithms for such problems, and possibly many other topology optimization problems.

Publication: IEICE TRANSACTIONS on Communications Vol.E79-B No.8 pp.1046-1053

Publication Date: 1996/08/25

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Type of Manuscript: Special Section PAPER (Special Issue on Multimedia on Demand)

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Yoshiaki TANAKA, Olivier BERLAGE, "Application of Genetic Algorithms to VOD Network Topology Optimization" in IEICE TRANSACTIONS on Communications, vol. E79-B, no. 8, pp. 1046-1053, August 1996, doi: .
Abstract: In this paper, we point out an architecture optimization problem for networks delivering services such as Video-On-Demand or, more precisely, two intertwined problems, i.e., the storage allocation of the videos among the storage nodes of the network and the choice of the network topology. We present and investigate the properties of a genetic algorithm which can handle such problems. This algorithm, as well as a greedy heuristics and simulated annealing, are then used to derive solutions in function of link and node cost parameters in a 36-node network. The results show that genetic algorithms are an effective class of algorithms for such problems, and possibly many other topology optimization problems.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/e79-b_8_1046/_p

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@ARTICLE{e79-b_8_1046,
author={Yoshiaki TANAKA, Olivier BERLAGE, },
journal={IEICE TRANSACTIONS on Communications},
title={Application of Genetic Algorithms to VOD Network Topology Optimization},
year={1996},
volume={E79-B},
number={8},
pages={1046-1053},
abstract={In this paper, we point out an architecture optimization problem for networks delivering services such as Video-On-Demand or, more precisely, two intertwined problems, i.e., the storage allocation of the videos among the storage nodes of the network and the choice of the network topology. We present and investigate the properties of a genetic algorithm which can handle such problems. This algorithm, as well as a greedy heuristics and simulated annealing, are then used to derive solutions in function of link and node cost parameters in a 36-node network. The results show that genetic algorithms are an effective class of algorithms for such problems, and possibly many other topology optimization problems.},
keywords={},
doi={},
ISSN={},
month={August},}

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TY - JOUR
TI - Application of Genetic Algorithms to VOD Network Topology Optimization
T2 - IEICE TRANSACTIONS on Communications
SP - 1046
EP - 1053
AU - Yoshiaki TANAKA
AU - Olivier BERLAGE
PY - 1996
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E79-B
IS - 8
JA - IEICE TRANSACTIONS on Communications
Y1 - August 1996
AB - In this paper, we point out an architecture optimization problem for networks delivering services such as Video-On-Demand or, more precisely, two intertwined problems, i.e., the storage allocation of the videos among the storage nodes of the network and the choice of the network topology. We present and investigate the properties of a genetic algorithm which can handle such problems. This algorithm, as well as a greedy heuristics and simulated annealing, are then used to derive solutions in function of link and node cost parameters in a 36-node network. The results show that genetic algorithms are an effective class of algorithms for such problems, and possibly many other topology optimization problems.
ER -