NLTA: Node and Link Topological Attributes Based Virtual Network Embedding

Abstract

Virtual Network Embedding (VNE) is the major challenge in Network Virtualization. Multiple VNE algorithms have been proposed in the literature. Most proposed VNE algorithms belong to the heuristic category. Heuristic algorithms mostly quantify certain node topological attributes and local node resources to rank (substrate and virtual) nodes before embedding each VN. Link topological attributes and global resources have not been quantified and assisted to rank nodes before. Thus leading to local optimum embedding and low VN acceptance ratio in the long run. To deal with this, we propose a new node ranking approach to rank all substrate and virtual nodes, covering multiple (node and link) topological attributes and global resources. Node and Link Topological Attributes based VNE algorithm, labeled as NLTA, is proposed on the basis of new node ranking approach. Extensive simulations demonstrate that NLTA outperforms four latest heuristic algorithms that consider certain node topological attributes and local node resources. For instance, average VN acceptance ratio of NLTA can increase up to 4% over the best behaved heuristic algorithm.