The Framework And Algorithms For The Survivable Mapping Of Virtual Network Onto A Substrate Network

Network virtualization serves as an effective method for providing a flexible and highly adaptable shared substrate network to satisfy the diversity of demands. However, the problem of efficiently mapping a virtual network onto a substrate network is intractable, as it is NP-hard. How to guarantee survivability of such a mapping efficiently is another great challenge. In this article, we investigate the survivable virtual network mapping (SVNM) problem and propose two kinds of algorithms for solving this problem efficiently. First, we formulate the model with a minimum-cost objective for the survivable network virtualization problem by mixed integer linear programming. We then devise two kinds of algorithms for solving the SVNM problem efficiently: (1) Lagrangian relaxation-based algorithms including LR-SVNM-M and LR-SVNM-D; (2) Heuristic algorithms including H-SVNM-D and H-SVNM-M. The simulation results show that these algorithms proposed in this study can be used to balance the tradeoff between time efficiency and the mapping cost.