Mapping strategy for virtual networks in one stage. Issue 14 (1st August 2019)

• Record Type: Journal Article
• Authors: Cao, Haotong; Wu, Shengchen; Guo, Yongan; Zhu, Hongbo; Yang, Longxiang
• Is Part Of: IET communications. Volume 13:Issue 14(2019)
• Page Start: 2207
• Page End: 2215
• Publication Date: 2019-08-01
• Subjects: computer networks -- virtualisation -- embedded systems -- resource allocation; mapping stage -- network virtualisation -- resource allocation problem -- link embeddings -- mixed integer linear programming approach -- heuristic algorithms -- one‐stage heuristic mapping algorithm -- VNE‐RTOS -- embedding revenues -- two‐stage heuristic embedding algorithms -- VNE algorithms -- embedding algorithms -- computation time -- dynamic VN service application -- network resources -- virtual network embedding; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2018.6175
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : In the area of network virtualisation, virtual network embedding (VNE) refers to the resource allocation problem. In the literature, researchers have proposed multiple VNE algorithms. These algorithms have the goal of accommodating as many requested virtual networks (VNs) as possible. However, most of prior embedding algorithms belong to the two‐stage (separated node and link embeddings) mapping algorithm category. Certain embedding algorithms embed each VN in one mapping stage by using mixed integer linear programming approach or graph theory, having very high computation time. There is a lack of heuristic algorithms, enabling to embed nodes and links per VN in one mapping stage. In addition, each requested VN embedding needs to be completed in polynomial time so as to be promoted to future dynamic VN service application and real‐time VNs embedding. Based on these backgrounds, the authors propose a novel real‐time and one‐stage heuristic mapping algorithm (VNE‐RTOS). Numerical evaluations are conducted to strengthen that VNE‐RTOS earns more embedding revenues by 8% over typical two‐stage heuristic embedding algorithms (e.g. VNE‐TAGRD) while achieving the same substrate resource utilisation.