2019
DOI: 10.1109/access.2018.2886270
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Topology-Oriented Virtual Network Embedding Approach for Data Centers

Abstract: 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 devel… Show more

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Cited by 12 publications
(2 citation statements)
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References 24 publications
(37 reference statements)
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“…Theorem 1) yields algorithms of practical significance only when the number of request nodes is small and in our computational study we restrict our attention to request graphs on less than 12 nodes. While this may be considered to be an unreasonably small number of nodes, many existing works on the VNEP [6,9] and its applications in data centers [30,31] consider requests of such size.…”
Section: Related Work and Noveltymentioning
confidence: 99%
“…Theorem 1) yields algorithms of practical significance only when the number of request nodes is small and in our computational study we restrict our attention to request graphs on less than 12 nodes. While this may be considered to be an unreasonably small number of nodes, many existing works on the VNEP [6,9] and its applications in data centers [30,31] consider requests of such size.…”
Section: Related Work and Noveltymentioning
confidence: 99%
“…Typical approaches apply a greedy algorithm that maps the VNFs requiring larger resources to the substrate nodes providing larger resources. Next, virtual links are mapped to the substrate paths using the shortest or k-shortest pathCao et al (2017);Zhang et al (2018);Yuan et al (2019). In the one-stage slice embedding approach, virtual links are mapped at the same time as VNFs.…”
mentioning
confidence: 99%