Risk-aware Data Replication (RDR), which replicates data at primary sites to nearby safe backup sites, has been proposed to mitigate service disruption in a disaster area even after a widespread disaster that damages a network and a primary site. RDR assigns a safe backup site to a primary site while considering damage risk for both the primary site and the backup candidate site. To minimize the damage risk of all site-pairs the Integer Programing Problem (IPP), which is a mathematical optimization problem, is applied. A challenge for RDR is to choose safe backup sites within a short computation time even for a huge number of sites. As described in this paper, we propose a Discreet method for RDR to surmount this hurdle. The Discreet method first judges the backup sites of a potentially unsafe primary site and avoids assigning a very safe primary site with a very safe backup site. We evaluated the computation time for site-paring and the data availability in the cases of Earthquake and Tsunami using basic disaster simulations. We confirmed that the computation rate of the proposed method is more than 1000 times faster than the existing method when the number of sites is greater than 1000. We also confirmed the data availability of the proposed method; it provides almost equal rates to existing methods of strict optimization. These results mean that the proposed method makes RDR more practical for massively multiple sites.
Takaki NAKAMURA
Tohoku University
Shinya MATSUMOTO
Hitachi, Ltd.
Hiroaki MURAOKA
Tohoku University
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Takaki NAKAMURA, Shinya MATSUMOTO, Hiroaki MURAOKA, "Discreet Method to Match Safe Site-Pairs in Short Computation Time for Risk-Aware Data Replication" in IEICE TRANSACTIONS on Information,
vol. E98-D, no. 8, pp. 1493-1502, August 2015, doi: 10.1587/transinf.2014EDP7439.
Abstract: Risk-aware Data Replication (RDR), which replicates data at primary sites to nearby safe backup sites, has been proposed to mitigate service disruption in a disaster area even after a widespread disaster that damages a network and a primary site. RDR assigns a safe backup site to a primary site while considering damage risk for both the primary site and the backup candidate site. To minimize the damage risk of all site-pairs the Integer Programing Problem (IPP), which is a mathematical optimization problem, is applied. A challenge for RDR is to choose safe backup sites within a short computation time even for a huge number of sites. As described in this paper, we propose a Discreet method for RDR to surmount this hurdle. The Discreet method first judges the backup sites of a potentially unsafe primary site and avoids assigning a very safe primary site with a very safe backup site. We evaluated the computation time for site-paring and the data availability in the cases of Earthquake and Tsunami using basic disaster simulations. We confirmed that the computation rate of the proposed method is more than 1000 times faster than the existing method when the number of sites is greater than 1000. We also confirmed the data availability of the proposed method; it provides almost equal rates to existing methods of strict optimization. These results mean that the proposed method makes RDR more practical for massively multiple sites.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.2014EDP7439/_p
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@ARTICLE{e98-d_8_1493,
author={Takaki NAKAMURA, Shinya MATSUMOTO, Hiroaki MURAOKA, },
journal={IEICE TRANSACTIONS on Information},
title={Discreet Method to Match Safe Site-Pairs in Short Computation Time for Risk-Aware Data Replication},
year={2015},
volume={E98-D},
number={8},
pages={1493-1502},
abstract={Risk-aware Data Replication (RDR), which replicates data at primary sites to nearby safe backup sites, has been proposed to mitigate service disruption in a disaster area even after a widespread disaster that damages a network and a primary site. RDR assigns a safe backup site to a primary site while considering damage risk for both the primary site and the backup candidate site. To minimize the damage risk of all site-pairs the Integer Programing Problem (IPP), which is a mathematical optimization problem, is applied. A challenge for RDR is to choose safe backup sites within a short computation time even for a huge number of sites. As described in this paper, we propose a Discreet method for RDR to surmount this hurdle. The Discreet method first judges the backup sites of a potentially unsafe primary site and avoids assigning a very safe primary site with a very safe backup site. We evaluated the computation time for site-paring and the data availability in the cases of Earthquake and Tsunami using basic disaster simulations. We confirmed that the computation rate of the proposed method is more than 1000 times faster than the existing method when the number of sites is greater than 1000. We also confirmed the data availability of the proposed method; it provides almost equal rates to existing methods of strict optimization. These results mean that the proposed method makes RDR more practical for massively multiple sites.},
keywords={},
doi={10.1587/transinf.2014EDP7439},
ISSN={1745-1361},
month={August},}
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TY - JOUR
TI - Discreet Method to Match Safe Site-Pairs in Short Computation Time for Risk-Aware Data Replication
T2 - IEICE TRANSACTIONS on Information
SP - 1493
EP - 1502
AU - Takaki NAKAMURA
AU - Shinya MATSUMOTO
AU - Hiroaki MURAOKA
PY - 2015
DO - 10.1587/transinf.2014EDP7439
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E98-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2015
AB - Risk-aware Data Replication (RDR), which replicates data at primary sites to nearby safe backup sites, has been proposed to mitigate service disruption in a disaster area even after a widespread disaster that damages a network and a primary site. RDR assigns a safe backup site to a primary site while considering damage risk for both the primary site and the backup candidate site. To minimize the damage risk of all site-pairs the Integer Programing Problem (IPP), which is a mathematical optimization problem, is applied. A challenge for RDR is to choose safe backup sites within a short computation time even for a huge number of sites. As described in this paper, we propose a Discreet method for RDR to surmount this hurdle. The Discreet method first judges the backup sites of a potentially unsafe primary site and avoids assigning a very safe primary site with a very safe backup site. We evaluated the computation time for site-paring and the data availability in the cases of Earthquake and Tsunami using basic disaster simulations. We confirmed that the computation rate of the proposed method is more than 1000 times faster than the existing method when the number of sites is greater than 1000. We also confirmed the data availability of the proposed method; it provides almost equal rates to existing methods of strict optimization. These results mean that the proposed method makes RDR more practical for massively multiple sites.
ER -