Survivable Virtual Network Embedding Problem Research Articles

Survivability-Enhanced Virtual Network Embedding Strategy in Virtualized Wireless Sensor Networks.

With the widespread application of wireless sensor networks (WSNs), WSN virtualization technology has received extensive attention. A key challenge in WSN virtualization is the survivable virtual network embedding (SVNE) problem which efficiently maps a virtual network on a WSN accounting for possible substrate failures. Aiming at the lack of survivability research towards physical sensor node failure in the virtualized sensor network, the SVNE problem is mathematically modeled as a mixed integer programming problem considering resource constraints. A heuristic algorithm—node reliability-aware backup survivable embedding algorithm (NCS)—is further put forward to solve this problem. Firstly, a node reliability-aware embedding method is presented for initial embedding. The resource reliability of underlying physical sensor nodes is evaluated and the nodes with higher reliability are selected as mapping nodes. Secondly, a fault recovery mechanism based on resource reservation is proposed. The critical virtual sensor nodes are recognized and their embedded physical sensor nodes are further backed up. When the virtual sensor network (VSN) fails caused by the failure physical node, the operation of the VSN is restored by backup switching. Finally, the experimental results show that the strategy put forward in this paper can effectively guarantee the survivability of the VSN, reduce the failure penalty caused by the physical sensor nodes failure, and improve the long-term operating income of infrastructure provider.

Virtual Network Survivability Through Joint Spare Capacity Allocation and Embedding

A key challenge in network virtualization is to efficiently map a virtual network (VN) on a substrate network (SN), while accounting for possible substrate failures. This is known as the survivable VN embedding (SVNE) problem. The state-of-the-art literature has studied the SVNE problem from infrastructure providers’ (InPs’) perspective, i.e., provisioning backup resources in the SN. A rather unexplored solution spectrum is to augment the VN with sufficient spare backup capacity to survive substrate failures and embed the resulting VN accordingly. Such augmentation enables InPs to offload failure recovery decisions to the VN operator, thus providing more flexible VN management. In this paper, we study the problem of jointly optimizing spare capacity allocation in a VN and embedding the VN to guarantee full bandwidth in the presence of multiple substrate link failures. We formulate the optimal solution to this problem as a quadratic integer program that we transform into an integer linear program. We also propose a heuristic algorithm to solve larger instances of the problem. Based on analytical study and simulation, our key findings are: 1) provisioning shared backup resources in the VN can yield ~33% more resource efficient embedding compared to doing the same at the SN level and 2) our heuristic allocates ~21% extra resources compared to the optimal, while executing several orders of magnitude faster.

Multi-Path Link Embedding for Survivability in Virtual Networks

Internet applications are deployed on the same network infrastructure, yet they have diverse performance and functional requirements. The Internet was not originally designed to support the diversity of current applications. Network virtualization enables heterogeneous applications and network architectures to coexist without interference on the same infrastructure. Embedding a virtual network (VN) into a physical network is a fundamental problem in network virtualization. A VN embedding that aims to survive physical (e.g., link) failures is known as the survivable VN embedding (SVNE). A key challenge in the SVNE problem is to ensure VN survivability with minimal resource redundancy. To address this challenge, we propose survivability in multi-path link embedding (SiMPLE). By exploiting path diversity in the physical network, SiMPLE provides guaranteed VN survivability against single link failure while incurring minimal resource redundancy. In case of multiple arbitrary link failures, SiMPLE provides maximal survivability to the VNs. We formulate this problem as an integer linear program and implement it using GNU linear programming kit. We propose a greedy proactive approach to solve larger instances of the problem in case of single link failures. In presence of more than one link failures, we propose a greedy reactive algorithm as an extension to the previous one, which opportunistically recovers the lost bandwidth in the VNs. Simulation results show that SiMPLE outperforms full backup and shared backup schemes for SVNE, and produces near-optimal results.

Dynamic recovery for survivable virtual network embedding

Network virtualization is a promising way to overcome the current ossification of the Internet. It is essential challenge to find effective, efficient and robust embedding algorithms for recovering virtual network. The virtual network mapping algorithm based on integer programming which was proposed months ago. But it did consider the faults of physical network resources, which is so called survivable virtual network embedding (VNE) problem. Previous strategies for enabling survivability in network virtualization focused on providing protection for the physical network or enhancing the virtual networks by providing backup physical resources in advance, and treated all the physical failures as link failures.In the article, a dynamic recovery method is proposed to solve the survivable virtual network embedding problem based on the integer programming VNE algorithm. The dynamic recovery method doesn't need to backup physical resources and it makes more substrate resources which can be used in the embedding. The dynamic recovery process will be activated only when physical failures occur. Different algorithms are used to recovery node and link failures. Simulations show that the method helps to recover almost all of physical failures by finding the substitute nodes and paths, and its performance is very close to that of pure VNE method without considering physical failures.