A efficient mapping algorithm with novel node-ranking approach for embedding virtual networks
journal contributionposted on 2018-01-18, 09:52 authored by Haotong Cao, Yongxu Zhu, Longxiang Yang, Gan Zheng
Virtual network embedding (VNE) problem has been widely accepted as an important aspect in network virtualization (NV) area: how to efficiently embed virtual networks, with node and link resource demands, onto the shared substrate network that has finite network resources. Previous VNE heuristic algorithms, only considering single network topology attribute and local resources 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, developed from the well-known Google PageRank algorithm, considers three essential topology attributes and global network resources information before conducting the embedding of given virtual network request (VNR). Numerical simulation results reveal that the VNE-TAGRD algorithm outperforms five typical and latest heuristic algorithms that only consider single network topology attribute and local resources of each node, such as long-term average VNR acceptance ratio and average revenue to cost ratio.
This work was supported in part by the National Natural Science Foundation of China under Grant 61372124 and Grant 61427801, in part by the National Basic Research Program of China (973 Program) under Grant 2013CB329104, and in part by the U.K. EPSRC under Grant EP/N007840/1.
- Mechanical, Electrical and Manufacturing Engineering