Minimizing Traffic Blocking and Inter-Crosstalk in Spatial Division Multiplexing over Elastic Optical Networking

As a promising solution, virtualization is vigorously developed to eliminate the ossification of traditional Internet infrastructure and enhance the flexibility in sharing the substrate network (SN) resources including computing, storage, bandwidth, etc. With network virtualization, cloud service providers can utilize the shared substrate resources to provision virtual networks (VNs) and facilitate a wide and diverse range of applications. As more and more internet applications migrate to the cloud, the resource efficiency and the survivability of VNs, such as single link failure or large-scale disaster survivability, have become crucial issues. Elastic optical networks have emerged in recent years as a strategy for dealing with the divergence of network application bandwidth needs. The network capacity has been constrained due to the usage of only two multiplexing dimensions. As transmission rates rise, so does the demand for network failure protection. Due to their end-to-end solutions, those safe-guarding paths are of particular importance among the protection methods. Due to their end-to-end solutions, those safeguarding paths are of particular importance among the protection methods. This paper presents approaches that provide a failure-independent route-protecting p-cycle for path protection in space-division multiplexed elastic optical networks. This letter looks at two SDM network challenges and presents a heuristic technique (k-shortest path) for each. In the first approach, we study a virtual network embedding (SVNE) problem and propose an algorithm for EONs, which can combat against single-link failures. We evaluate the proposed POPETA algorithm and compare its performance with some counterpart algorithms. Simulation results demonstrate that the proposed algorithm can achieve satisfactory performance in terms of spectrum utilization and blocking ratio, even if with a higher backup redundancy ratio.