The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Cet article propose une approche d'optimisation qui conçoit le réseau de secours avec la capacité totale minimale pour protéger le réseau principal contre les défaillances aléatoires de plusieurs liaisons avec une probabilité de défaillance de liaison. Dans l'approche conventionnelle, le routage dans le réseau primaire n'est pas considéré comme un facteur de minimisation de la capacité totale du réseau de secours. Considérer le routage principal comme une variable lors du choix du réseau de secours peut réduire la capacité totale du réseau de secours par rapport à l'approche conventionnelle. Le problème d'optimisation examiné ici utilise une optimisation robuste pour fournir des garanties probabilistes de survie pour différentes capacités de liaison dans le réseau principal. L'approche proposée formule le problème d'optimisation comme un problème de programmation linéaire en nombres entiers mixtes (MILP) avec optimisation robuste. Une implémentation heuristique est introduite pour l'approche proposée car le problème MILP ne peut pas être résolu en temps pratique lorsque la taille du réseau augmente. Les résultats numériques montrent que l'approche proposée peut atteindre une capacité totale inférieure dans le réseau de secours par rapport à l'approche conventionnelle.
Soudalin KHOUANGVICHIT
The University of Electro-Communications
Nattapong KITSUWAN
The University of Electro-Communications
Eiji OKI
Kyoto University
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Soudalin KHOUANGVICHIT, Nattapong KITSUWAN, Eiji OKI, "Optimization Approach to Minimize Backup Capacity Considering Routing in Primary and Backup Networks for Random Multiple Link Failures" in IEICE TRANSACTIONS on Communications,
vol. E103-B, no. 7, pp. 726-735, July 2020, doi: 10.1587/transcom.2019EBP3173.
Abstract: This paper proposes an optimization approach that designs the backup network with the minimum total capacity to protect the primary network from random multiple link failures with link failure probability. In the conventional approach, the routing in the primary network is not considered as a factor in minimizing the total capacity of the backup network. Considering primary routing as a variable when deciding the backup network can reduce the total capacity in the backup network compared to the conventional approach. The optimization problem examined here employs robust optimization to provide probabilistic survivability guarantees for different link capacities in the primary network. The proposed approach formulates the optimization problem as a mixed integer linear programming (MILP) problem with robust optimization. A heuristic implementation is introduced for the proposed approach as the MILP problem cannot be solved in practical time when the network size increases. Numerical results show that the proposed approach can achieve lower total capacity in the backup network than the conventional approach.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2019EBP3173/_p
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@ARTICLE{e103-b_7_726,
author={Soudalin KHOUANGVICHIT, Nattapong KITSUWAN, Eiji OKI, },
journal={IEICE TRANSACTIONS on Communications},
title={Optimization Approach to Minimize Backup Capacity Considering Routing in Primary and Backup Networks for Random Multiple Link Failures},
year={2020},
volume={E103-B},
number={7},
pages={726-735},
abstract={This paper proposes an optimization approach that designs the backup network with the minimum total capacity to protect the primary network from random multiple link failures with link failure probability. In the conventional approach, the routing in the primary network is not considered as a factor in minimizing the total capacity of the backup network. Considering primary routing as a variable when deciding the backup network can reduce the total capacity in the backup network compared to the conventional approach. The optimization problem examined here employs robust optimization to provide probabilistic survivability guarantees for different link capacities in the primary network. The proposed approach formulates the optimization problem as a mixed integer linear programming (MILP) problem with robust optimization. A heuristic implementation is introduced for the proposed approach as the MILP problem cannot be solved in practical time when the network size increases. Numerical results show that the proposed approach can achieve lower total capacity in the backup network than the conventional approach.},
keywords={},
doi={10.1587/transcom.2019EBP3173},
ISSN={1745-1345},
month={July},}
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TY - JOUR
TI - Optimization Approach to Minimize Backup Capacity Considering Routing in Primary and Backup Networks for Random Multiple Link Failures
T2 - IEICE TRANSACTIONS on Communications
SP - 726
EP - 735
AU - Soudalin KHOUANGVICHIT
AU - Nattapong KITSUWAN
AU - Eiji OKI
PY - 2020
DO - 10.1587/transcom.2019EBP3173
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E103-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 2020
AB - This paper proposes an optimization approach that designs the backup network with the minimum total capacity to protect the primary network from random multiple link failures with link failure probability. In the conventional approach, the routing in the primary network is not considered as a factor in minimizing the total capacity of the backup network. Considering primary routing as a variable when deciding the backup network can reduce the total capacity in the backup network compared to the conventional approach. The optimization problem examined here employs robust optimization to provide probabilistic survivability guarantees for different link capacities in the primary network. The proposed approach formulates the optimization problem as a mixed integer linear programming (MILP) problem with robust optimization. A heuristic implementation is introduced for the proposed approach as the MILP problem cannot be solved in practical time when the network size increases. Numerical results show that the proposed approach can achieve lower total capacity in the backup network than the conventional approach.
ER -