Virtual Network Embedding Through Topology-Aware Node Ranking
Virtualizing and sharing networked resources have become a growing trend that reshapes the computing and networking architectures. Embedding multiple Virtual Networks (VNs) on a shared substrate is a challenging problem on cloud computing platforms and large-scale sliceable network testbeds. In this paper the authors apply the Markov Random Walk (RW) model to rank a network node based on its resource and topological attributes. This novel topology-aware node ranking measure reflects the relative importance of the node. Using node ranking the authors devise two VN embedding algorithms.