Topology-oriented virtual network embedding approach for data centers

Yuan, Ying, Wang, Cong, Peng, Sancheng and Sood, Keshav 2018, Topology-oriented virtual network embedding approach for data centers, IEEE access, vol. 7, pp. 2429-2438, doi: 10.1109/ACCESS.2018.2886270.

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Title Topology-oriented virtual network embedding approach for data centers
Author(s) Yuan, Ying
Wang, Cong
Peng, Sancheng
Sood, Keshav
Journal name IEEE access
Volume number 7
Start page 2429
End page 2438
Total pages 10
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2018-12-11
ISSN 2169-3536
Keyword(s) Science & Technology
Technology
Computer Science, Information Systems
Engineering, Electrical & Electronic
Telecommunications
Computer Science
Engineering
Data center
virtual resource allocation
virtual network embedding
discrete particle swarm optimization
NODE-RANKING APPROACH
MAPPING ALGORITHM
Summary © 2018 IEEE. Currently, data centers have become an attractive candidate for users that require IT resources in the form of virtual networks to run their applications. Optimal mapping of the virtual network on the top of the substrate network with resource constraint is called virtual network embedding (VNE) problem. Most of the VNE algorithms are general algorithms for random topology and not suitable for data centers due to particular topological characteristics. To solve the VNE problem in data centers, this paper develops a topology-oriented algorithm based on the Discrete Particle Swarm Optimization (DPSO). We first develop a maximum spanning algorithm to compute the ranking of virtual nodes based on, not only its bandwidth and degree, but also its connectivity in the entire virtual network. Then, the virtual networks are embedded onto the substrate network according to the connectivity ranking result by a DPSO-based algorithm, in which we also propose a topological heuristic information of substrate network and combine it into the particle search process for boosting convergence speed and revenue/cost ratio of substrate network. The evaluation results show that the proposed algorithm can improve the optimization performance of VNE by comparing with a few existing algorithms.
Language eng
DOI 10.1109/ACCESS.2018.2886270
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2018, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30116848

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