Telecommunications

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 com-puting platforms and large-scale sliceable network testbeds. In this paper we apply the Markov Random Walk (RW) model to rank a network node based on its resource and topological attributes. This novel topology-aware node rank-ing measure reflects the relative importance of the node. Us-ing node ranking we devise two VN embedding algorithms. The first algorithm maps virtual nodes to substrate nodes according to their ranks, then embeds the virtual links be-tween the mapped nodes by finding shortest paths with un-splittable paths and solving the multi-commodity flow prob-lem with splittable paths. The second algorithm is a back-tracking VN embedding algorithm based on breadth-first search, which embeds the virtual nodes and links during the same stage using node ranks. Extensive simulation experi-ments show that the topology-aware node rank is a better resource measure and the proposed RW-based algorithms in-crease the long-term average revenue and acceptance ratio compared to the existing embedding algorithms