Adaptive Weights-based Dynamic Resource Provisioning in Space Division Multiplexed-Elastic Optical Networks (SDM-EONs)

One of the core research issues in Space Division Multiplexed-Elastic Optical Networks (SDM-EON) is the Routing, Space, and Spectrum assignment (RSSA) to support maximum possible traffic. Due to the addition of spatial di-mension, additional constraints and design issues crop up for the resource provisioning in SDM-EON. There could be severe fragmentation in the network spectrum along with the crosstalk impairment among cores leading to unavailability of the resources following RSSA constraints. It limits the efficient utilization of the available capacity in SDM-EON. We propose an Adaptive Weights-based Dynamic Resource Assignment (AW-DRA) technique using SDM-EON link cost parameters and their respective weights. Each link periodically adapts the weights, conforming with the link spectral state, using Teaching Learning-based Optimization (TLBO) approach. We compare the performance of the proposed technique with two other benchmark techniques using simulations. The results demonstrate that the proposed AW-DRA technique performs significantly better in connection blocking and spectrum utilization.