An efficient embedding algorithm for virtual network via exploiting topology attributes and global network resources

Haotong Cao, Longxiang Yang, Hongbo Zhu
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引用次数: 1

Abstract

Virtual Network Embedding (VNE) is one of the longstanding challenges in Network Virtualization: how to efficiently embed multiple virtual networks (VNs), with node-link resource requirements, onto the shared substrate network, having finite underlying resources. Proposed algorithms are heuristic in the literature. Most heuristic VNE algorithms, only considering single network topology attribute and local node resources to rank nodes, will lead to low resource utilization of substrate network and low average VN acceptance ratio in the long term. To deal with this issue, this paper proposes another efficient heuristic algorithm VNE-TAGNR, adopting a novel node-ranking approach in the node mapping stage and coordinating the following link mapping stage. In the node-ranking approach, three fundamental Topology Attributes and Global Network Resources (TAGNR) are considered and quantified. Numerical simulation results vividly reveal that the proposed VNE-TAGNR algorithm outperforms four typical and state-of-the-art heuristic algorithms, in terms of average VN acceptance ratio, average node / link utilization and average revenue / cost.
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一种利用拓扑属性和全局网络资源的高效虚拟网络嵌入算法
虚拟网络嵌入(VNE)是网络虚拟化中长期存在的挑战之一:如何有效地将具有节点链路资源需求的多个虚拟网络(VNs)嵌入到底层资源有限的共享底层网络中。在文献中提出的算法是启发式的。大多数启发式VNE算法仅考虑单个网络拓扑属性和本地节点资源对节点进行排序,导致底层网络资源利用率低,长期平均VN接受率低。针对这一问题,本文提出了另一种高效的启发式算法VNE-TAGNR,在节点映射阶段采用新颖的节点排序方法,协调后续的链路映射阶段。在节点排序方法中,考虑并量化了三个基本拓扑属性和全局网络资源(TAGNR)。数值仿真结果生动地表明,提出的VNE-TAGNR算法在平均VN接受率、平均节点/链路利用率和平均收益/成本方面都优于四种典型的启发式算法。
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