Efficient Virtual Network Embedding with Node Ranking and Intelligent Link Mapping

Network virtualization (NV) is emerged as a key enabler for the success of the future virtualized networks (e.g. 5G networks and smart Internet of Things (IoT)). Virtual Network Embedding (VNE) that addresses the embedding problems of heterogeneous virtual networks (VNs) onto a physical infrastructure is a main challenge in NV. Network topology attributes and network resource-considered (NTANRC) algorithm is a virtual node mapping mechanism that considers essential network features and global network resources for ranking both substrate and virtual nodes prior to embedding each given virtual network request (VNR). In this paper, we propose NTANRC combined with a distributed parallel Genetic Algorithm (GA) for virtual link mapping, namely NTANRC-GA, to solve online VNE problem. Extensive evaluation results show that our proposed solution not only achieves better performance compared to state-of-the-art VNE algorithms, but also challenges the rapid speed of shortest path (SP) method. NTANRC algorithm and the parallel GA-based algorithm are reverse compliments of each other to achieve an efficient VNE solution.