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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Topological Embedding Feature Based Resource Allocation in Network Virtualization
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Topological Embedding Feature Based Resource Allocation in Network Virtualization

机译:网络虚拟化中基于拓扑嵌入特征的资源分配

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摘要

Virtualization provides a powerful way to run multiple virtual networks on a shared substrate network, which needs accurate and efficient mathematical models. Virtual network embedding is a challenge in network virtualization. In this paper, considering the degree of convergence when mapping a virtual network onto substrate network, we propose a new embedding algorithm based on topology mapping convergence-degree. Convergence-degree means the adjacent degree of virtual network’s nodes when they are mapped onto a substrate network. The contributions of our method are as below. Firstly, we map virtual nodes onto the substrate nodes with the maximum convergence-degree. The simulation results show that our proposed algorithm largely enhances the network utilization efficiency and decreases the complexity of the embedding problem. Secondly, we define the load balance rate to reflect the load balance of substrate links. The simulation results show our proposed algorithm achieves better load balance. Finally, based on the feature of star topology, we further improve our embedding algorithm and make it suitable for application in the star topology. The test result shows it gets better performance than previous works.
机译:虚拟化提供了一种强大的方式,可以在共享的基础网络上运行多个虚拟网络,这需要准确而高效的数学模型。虚拟网络嵌入是网络虚拟化中的一个挑战。本文考虑了虚拟网络映射到基层网络时的收敛程度,提出了一种基于拓扑映射收敛度的嵌入算法。收敛度是指虚拟网络节点映射到基础网络时的相邻度。我们的方法的贡献如下。首先,我们以最大收敛度将虚拟节点映射到基板节点上。仿真结果表明,该算法大大提高了网络利用率,降低了嵌入问题的复杂度。其次,我们定义负载平衡率以反映基板链接的负载平衡。仿真结果表明,本文提出的算法实现了较好的负载均衡。最后,根据星形拓扑的特点,进一步改进了嵌入算法,使其适用于星形拓扑。测试结果表明,它比以前的作品具有更好的性能。

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