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Proceedings Paper

Efficient algorithms for survivable virtual network embedding
Author(s): Gang Sun; Hongfang Yu; Lemin Li; Vishal Anand; Hao Di; Xiujiao Gao
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Paper Abstract

Network Virtualization Technology is serving as an effective method for providing a flexible and highly adaptable shared substrate network to satisfy the diversity of demands. But the problem of efficiently embedding Virtual Network (VN) onto substrate network is intractable since it is NP-hard. How to guarantee survivability of the embedding efficiently is another great challenge. In this paper, we investigate the Survivable Virtual Network Embedding (SVNE) problem and propose two efficient algorithms for solving this problem efficiently. Firstly, we formulate the model with minimum-cost objective of survivable network virtualization problem by Mixed Integer Linear Programming (MILP). We then devise two efficient relaxation-based algorithms for solving survivable virtual network embedding problem: (1) Lagrangian Relaxation based algorithm, called LR-SVNE in this paper; (2) Decomposition based algorithm called DSVNE in this paper. The results of simulation experiments show that these two algorithms both have good performance on time efficiency but LR-SVNE can guarantee the solution converge to optimal one under small scale substrate network.

Paper Details

Date Published: 11 January 2011
PDF: 7 pages
Proc. SPIE 7989, Network Architectures, Management, and Applications VIII, 79890K (11 January 2011); doi: 10.1117/12.887651
Show Author Affiliations
Gang Sun, Univ. of Electronic Science and Technology of China (China)
Hongfang Yu, Univ. of Electronic Science and Technology of China (China)
Lemin Li, Univ. of Electronic Science and Technology of China (China)
Vishal Anand, The College at Brockport, SUNY (United States)
Hao Di, Univ. of Electronic Science and Technology of China (China)
Xiujiao Gao, Univ. of Electronic Science and Technology of China (China)


Published in SPIE Proceedings Vol. 7989:
Network Architectures, Management, and Applications VIII
Lena Wosinska, Editor(s)

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