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Node-Fusion: Topology-aware virtual network embedding algorithm for repeatable virtual network mapping over substrate nodes

机译:节点融合:用于基板节点的可重复虚拟网络映射的拓扑知识虚拟网络嵌入算法

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摘要

Cloud computing has become a new Internet application model, where network virtualization is recognized as an important technology for allowing multiple heterogeneous virtual networks (VNs) to coexist on a shared substrate network (SN). As demands in cloud computing increase, the scale of VN greatly increases as well, and providing an end-to-end SN to embed VNs in terms of scale is difficult. To utilize SN resources fully, we devise a topology-aware Node-Fusion algorithm, which is different from the traditional virtual network embedding (VNE) algorithms, for repeatable VNE over substrate nodes problem. We rank the resource of nodes through a novel solution by considering the CPU and bandwidth of adjacent link capacity and the number of adjacent links of each node as resources, and rank a node on the basis of resources. Furthermore, we embed several virtual nodes into the same substrate node together in accordance with Node-Fusion interconnection value during the node mapping process, which can greatly improve the success ratio of the subsequent link mapping phase. Evaluation results confirm that Node-Fusion outperforms traditional classical heuristics (Link-opt, Node-opt, and ORSTA), which are modified to fit into our model, with regard to acceptance ratio, long-term revenue, long-term cost, and revenue-cost ratio.
机译:云计算已成为新的互联网应用模型,其中网络虚拟化被识别为允许多个异构虚拟网络(VNS)在共享基板网络(SN)上共存的重要技术。随着云计算的需求增加,VN的规模也大大增加,并且在规模方面提供了端到端的SN以嵌入VNS是困难的。要充分利用SN资源,我们设计了一种拓扑感知节点融合算法,它与传统的虚拟网络嵌入(VNE)算法不同,可重复VNE在基板节点上的问题。我们通过考虑相邻链路容量的CPU和带宽以及每个节点作为资源的相邻链路的数量,并基于资源对节点进行排序,通过新的解决方案排序节点的资源。此外,我们根据节点映射过程期间将若干虚拟节点嵌入到相同的基板节点中,可以大大提高后续链路映射阶段的成功比率。评估结果证实,节点融合优于传统的经典启发式(LINK-OPT,Node-Opt和Orsta),这些内容被修改为适合我们的模型,关于接受比率,长期收入,长期成本和收入成本比率。

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