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 présente un modèle analytique qui donne l'indisponibilité d'une fonction réseau lorsque chaque serveur de sauvegarde peut protéger deux fonctions et récupérer l'une d'entre elles. Des travaux antérieurs décrivent un modèle pour traiter le cas où chaque fonction ne peut être protégée que par un seul serveur. Dans notre modèle, nous permettons à chaque fonction d'être protégée par plusieurs serveurs pour garantir la disponibilité des fonctions. Cela nous oblige à connaître les états réalisables d’un composant connecté et ses transitions d’état. En adoptant la méthode diviser pour régner, nous énumérons les états réalisables d’un composant connecté. Nous classons ensuite ses transitions d'état. Sur la base des états réalisables obtenus et de la classification des transitions d'état, nous énumérons les états réalisables entrant et sortant d'un état général, les taux de transfert et les conditions. Avec ces informations, nous générons plusieurs équations sur les transitions d'état. Enfin, en les résolvant, on obtient les probabilités qu'un composant connecté soit dans chaque état et on calcule l'indisponibilité d'une fonction. Les résultats numériques montrent que l'indisponibilité moyenne d'une fonction est réduite de 18% et 5.7% dans nos deux cas examinés en permettant à chaque fonction d'être protégée par plusieurs serveurs.
Risa FUJITA
Kyoto University
Fujun HE
Kyoto University
Eiji OKI
Kyoto University
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Risa FUJITA, Fujun HE, Eiji OKI, "Analytical Model of Middlebox Unavailability under Shared Protection Allowing Multiple Backups" in IEICE TRANSACTIONS on Communications,
vol. E104-B, no. 9, pp. 1147-1158, September 2021, doi: 10.1587/transcom.2020EBP3176.
Abstract: This paper presents an analytical model that yields the unavailability of a network function when each backup server can protect two functions and can recover one of them. Previous work describes a model to deal with the case that each function can be protected only by one server. In our model, we allow each function to be protected by multiple servers to ensure function availability. This requires us to know the feasible states of a connected component and its state transitions. By adopting the divide-and-conquer method, we enumerate the feasible states of a connected component. We then classify its state transitions. Based on the obtained feasible states and the classification of the state transitions, we enumerate the feasible states incoming to and outgoing from a general state, the transfer rates, and the conditions. With those informations, we generate multiple equations about the state transitions. Finally, by solving them, we obtain the probabilities that a connected component is in each state and calculate the unavailability of a function. Numerical results show that the average unavailability of a function is reduced by 18% and 5.7% in our two examined cases by allowing each function to be protected by multiple servers.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2020EBP3176/_p
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@ARTICLE{e104-b_9_1147,
author={Risa FUJITA, Fujun HE, Eiji OKI, },
journal={IEICE TRANSACTIONS on Communications},
title={Analytical Model of Middlebox Unavailability under Shared Protection Allowing Multiple Backups},
year={2021},
volume={E104-B},
number={9},
pages={1147-1158},
abstract={This paper presents an analytical model that yields the unavailability of a network function when each backup server can protect two functions and can recover one of them. Previous work describes a model to deal with the case that each function can be protected only by one server. In our model, we allow each function to be protected by multiple servers to ensure function availability. This requires us to know the feasible states of a connected component and its state transitions. By adopting the divide-and-conquer method, we enumerate the feasible states of a connected component. We then classify its state transitions. Based on the obtained feasible states and the classification of the state transitions, we enumerate the feasible states incoming to and outgoing from a general state, the transfer rates, and the conditions. With those informations, we generate multiple equations about the state transitions. Finally, by solving them, we obtain the probabilities that a connected component is in each state and calculate the unavailability of a function. Numerical results show that the average unavailability of a function is reduced by 18% and 5.7% in our two examined cases by allowing each function to be protected by multiple servers.},
keywords={},
doi={10.1587/transcom.2020EBP3176},
ISSN={1745-1345},
month={September},}
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TY - JOUR
TI - Analytical Model of Middlebox Unavailability under Shared Protection Allowing Multiple Backups
T2 - IEICE TRANSACTIONS on Communications
SP - 1147
EP - 1158
AU - Risa FUJITA
AU - Fujun HE
AU - Eiji OKI
PY - 2021
DO - 10.1587/transcom.2020EBP3176
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E104-B
IS - 9
JA - IEICE TRANSACTIONS on Communications
Y1 - September 2021
AB - This paper presents an analytical model that yields the unavailability of a network function when each backup server can protect two functions and can recover one of them. Previous work describes a model to deal with the case that each function can be protected only by one server. In our model, we allow each function to be protected by multiple servers to ensure function availability. This requires us to know the feasible states of a connected component and its state transitions. By adopting the divide-and-conquer method, we enumerate the feasible states of a connected component. We then classify its state transitions. Based on the obtained feasible states and the classification of the state transitions, we enumerate the feasible states incoming to and outgoing from a general state, the transfer rates, and the conditions. With those informations, we generate multiple equations about the state transitions. Finally, by solving them, we obtain the probabilities that a connected component is in each state and calculate the unavailability of a function. Numerical results show that the average unavailability of a function is reduced by 18% and 5.7% in our two examined cases by allowing each function to be protected by multiple servers.
ER -