Topology attribute and global resource-driven virtual network embedding algorithm via novel node-ranking approach

Abstract

Virtual Network Embedding (VNE) problem has been widely considered as an important challenge in Network Virtualization (NV): how to embed virtual networks onto the shared substrate network effectively and efficiently. Previous VNE algorithms, only considering single network topology attribute and local resource of each node, may lead to inefficient resource utilization of the substrate network in the long term. To address this issue, a Topology Attribute and Global Resource-Driven VNE algorithm (VNE-TAGRD), adopting a novel node-ranking approach, is proposed in this paper. The novel node-ranking approach, stimulating from the well-known Google PageRank algorithm, considers three essential topology attributes and global network resource information. Numerical simulation results reveal that the proposed VNE-TAGRD outperforms four related and up-to-date heuristic algorithms that only consider single network topology attribute and local resources of each node, in terms of long-term virtual network request acceptance ratio, average revenue to cost ratio.