Location Aware and Node Ranking Value-Assisted Embedding Algorithm for One-Stage Embedding in Multiple Distributed Virtual Network Embedding

Network virtualization (NV) is one crucial attribute for the next-generation network. Virtual network embedding (VNE) is known to be the resource allocation problem in NV content. Since 2008, researchers have proposed multiple embedding algorithms to embed VNs onto the underlying physical networks. Considering the NP-hard nature of VNE, most of the prior algorithms focus on embedding each VN in two separated embedding stages (separated node and link embeddings). Some embedding algorithms embed each VN in one embedding stage by adopting a mixed integer linear programming approach or game theory or sub-graph isomorphism, trapped in high computation time. These algorithms embed the VN in one centralized substrate network (SN), while, in real networking environment, each VN must be embedded among multiple SNs. Each substrate node is geographically distributed in a different location. In order to address these issues, we propose a Location-Aware and Node Ranking Value Assisted embedding algorithm (labeled as LANRVA-VNE). The LANRVA-VNE conducts each VN embedding in one embedding stage. In addition, the LANRVA-VNE is able to embed each requested VN service among multiple distributed SNs in polynomial time, aiming at promoting future dynamic VN service implementation. Main evaluation results reveal that the LANRVA-VNE significantly improves VN acceptance ratio by at least 10% over the typical two-stage algorithms (e.g., VNE-NTANRC-S, RW-SP, and ViNE-SP).