Modulation-Adaptive Resource Allocation Integrating ML-based Routing and QoT Estimation for Elastic Optical Network Planning

We propose a pointer network-based joint routing, modulation format, and spectrum allocation (PtrNet-RMSA) scheme to optimize the network capacity in elastic optical networks (EONs). Specifically, for a service request, EON spectra are first split into multiple spectrum window planes (SWPs), regarding various numbers of contained frequency slots (FSs). Then, over each SWP, a lightpath with an optimal estimated quality of transmission (QoT) is generated using a PtrNet-based routing agent. Further, different modulation formats are verified for the generated lightpath over the considered SWP, with respect to a calculated QoT threshold, to check whether a specific preforward error correction (FEC) requirement can be satisfied. Finally, two heuristic approaches, first fit and highest fit, are applied in the joint RMSA to select an optimal lightpath of an SWP and modulation format. To evaluate the efficiency of the PtrNet-RMSA scheme, extensive simulations were conducted in EONs with dynamic traffic. Results show that the proposed PtrNet-RMSA scheme can significantly improve the network capacity with various network topologies, compared with two benchmarks.