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A 2-Layers Virtual Network Mapping Algorithm Based on Node Attribute and Network Simplex

delete2018-01-01
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OA
AI
Q
Quan Zheng *
L
Li Jun
H
Hongliang Tian
Z
Zhizhen Wang
S
Song Wang
DOI:10.1109/ACCESS.2018.2883251delete
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摘要

摘要

En 中文
Network virtualization is one of the most important techniques to overcome Internet ossification, which can enable multiple networks to run on a common infrastructure. Virtual network mapping is a key process of network virtualization to efficiently map virtual network onto the substrate network within constraints of node and link resource. However, previous VNM heuristic algorithms completely separate the node mapping stage from link mapping stage and ignore the effect of link mapping results on physical node ranking, which may lead to higher mapping cost and distributed distribution of virtual nodes on the substrate network. The shortest path algorithm is used at most to resolve virtual link mapping which results in longer mapping time. To address these issues, a two-layer virtual network mapping algorithm named simplex-VNM is proposed based on node attribute and network simplex in this paper. In node mapping layer, a new node ranking approach which considers topology attributes, global network resources, and mapped physical node information provides candidate nodes and node mapping cost for link mapping layer. Then, in link mapping layer, network simplex algorithm which has smaller time complexity compared to traditional shortest path algorithms has been introduced to find the optimal link mapping solution under the result of node mapping layer. Finally, according to the results of two layers, the virtual node and relevant links will be mapped with minimal total mapping cost. Extensive simulation results have demonstrated that our proposed method behaves better than four other algorithms that consider node attribute and use shortest path algorithm in terms of total mapping cost and mapping time.
Keyword:
Virtual network mapping
network simplex
node attribute
node-ranking approach
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期刊

IEEE Access 封面图
IEEE Access
IF:
3.6
论文数:
9.8W
被引数:
29.4W

机构

U
university of science & technology of china, cas
学者数:
3.2W
论文数: 2.7W
被引数: 74
C
chinese academy of sciences
学者数:
56.7W
论文数: 45.0W
被引数: 704
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