IEICE TRANSACTIONS on Communications
Virtual Network Embedding across Multiple Domains with Secure Multi-Party Computation
Summary :
Network virtualization is one of the promising technologies that can increase flexibility, diversity, and manageability of networks. Building optimal virtual networks across multiple domains is getting much attention, but existing studies were based on an unrealistic assumption, that is, providers' private information can be disclosed; as is well known, providers never actually do that. In this paper, we propose a new method that solves this multi-domain problem without revealing providers' private information. Our method uses an advanced secure computation technique called multi-party computation (MPC). Although MPC enables existing unsecured methods to optimize virtual networks securely, it requires very large time to finish the optimization due to the MPC's complex distributed protocols. Our method, in contrast, is designed to involve only a small number of MPC operations to find the optimal solution, and it allows providers to execute a large part of the optimization process independently without heavy distributed protocols. Evaluation results show that our method is faster than an existing method enhanced with MPC by several orders of magnitude. We also unveil that our method has the same level of embedding cost.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E98-B No.3 pp.437-448
- Publication Date
- 2015/03/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E98.B.437
- Type of Manuscript
- PAPER
- Category
- Network
Authors
Toru MANO
NTT Corporation
Takeru INOUE
NTT Corporation
Kimihiro MIZUTANI
NTT Corporation
Osamu AKASHI
NTT Corporation
Keyword
Latest Issue
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Toru MANO, Takeru INOUE, Kimihiro MIZUTANI, Osamu AKASHI, "Virtual Network Embedding across Multiple Domains with Secure Multi-Party Computation" in IEICE TRANSACTIONS on Communications,
vol. E98-B, no. 3, pp. 437-448, March 2015, doi: 10.1587/transcom.E98.B.437.
Abstract: Network virtualization is one of the promising technologies that can increase flexibility, diversity, and manageability of networks. Building optimal virtual networks across multiple domains is getting much attention, but existing studies were based on an unrealistic assumption, that is, providers' private information can be disclosed; as is well known, providers never actually do that. In this paper, we propose a new method that solves this multi-domain problem without revealing providers' private information. Our method uses an advanced secure computation technique called multi-party computation (MPC). Although MPC enables existing unsecured methods to optimize virtual networks securely, it requires very large time to finish the optimization due to the MPC's complex distributed protocols. Our method, in contrast, is designed to involve only a small number of MPC operations to find the optimal solution, and it allows providers to execute a large part of the optimization process independently without heavy distributed protocols. Evaluation results show that our method is faster than an existing method enhanced with MPC by several orders of magnitude. We also unveil that our method has the same level of embedding cost.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E98.B.437/_p
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@ARTICLE{e98-b_3_437,
author={Toru MANO, Takeru INOUE, Kimihiro MIZUTANI, Osamu AKASHI, },
journal={IEICE TRANSACTIONS on Communications},
title={Virtual Network Embedding across Multiple Domains with Secure Multi-Party Computation},
year={2015},
volume={E98-B},
number={3},
pages={437-448},
abstract={Network virtualization is one of the promising technologies that can increase flexibility, diversity, and manageability of networks. Building optimal virtual networks across multiple domains is getting much attention, but existing studies were based on an unrealistic assumption, that is, providers' private information can be disclosed; as is well known, providers never actually do that. In this paper, we propose a new method that solves this multi-domain problem without revealing providers' private information. Our method uses an advanced secure computation technique called multi-party computation (MPC). Although MPC enables existing unsecured methods to optimize virtual networks securely, it requires very large time to finish the optimization due to the MPC's complex distributed protocols. Our method, in contrast, is designed to involve only a small number of MPC operations to find the optimal solution, and it allows providers to execute a large part of the optimization process independently without heavy distributed protocols. Evaluation results show that our method is faster than an existing method enhanced with MPC by several orders of magnitude. We also unveil that our method has the same level of embedding cost.},
keywords={},
doi={10.1587/transcom.E98.B.437},
ISSN={1745-1345},
month={March},}
Copy
TY - JOUR
TI - Virtual Network Embedding across Multiple Domains with Secure Multi-Party Computation
T2 - IEICE TRANSACTIONS on Communications
SP - 437
EP - 448
AU - Toru MANO
AU - Takeru INOUE
AU - Kimihiro MIZUTANI
AU - Osamu AKASHI
PY - 2015
DO - 10.1587/transcom.E98.B.437
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E98-B
IS - 3
JA - IEICE TRANSACTIONS on Communications
Y1 - March 2015
AB - Network virtualization is one of the promising technologies that can increase flexibility, diversity, and manageability of networks. Building optimal virtual networks across multiple domains is getting much attention, but existing studies were based on an unrealistic assumption, that is, providers' private information can be disclosed; as is well known, providers never actually do that. In this paper, we propose a new method that solves this multi-domain problem without revealing providers' private information. Our method uses an advanced secure computation technique called multi-party computation (MPC). Although MPC enables existing unsecured methods to optimize virtual networks securely, it requires very large time to finish the optimization due to the MPC's complex distributed protocols. Our method, in contrast, is designed to involve only a small number of MPC operations to find the optimal solution, and it allows providers to execute a large part of the optimization process independently without heavy distributed protocols. Evaluation results show that our method is faster than an existing method enhanced with MPC by several orders of magnitude. We also unveil that our method has the same level of embedding cost.
ER -
English
