ABACUS: A Joint Optimal Dynamic RMLSA in Elastic Optical Networks

The optimal Routing and Spectrum Assignment (RSA) presents a significant challenge in the Elastic Optical Networks (EONs). Integrating adaptive modulation formats into the RSA problem, i.e. Routing, Modulation Level and Spectrum Assignment (RMLSA), increases allocation options and heightens complexity. The conventional RSA approach involves pre-determining fixed paths and then allocate spectrum within them separately. However, expansion of path set for optimality may not be advisable due to the substantial increase in paths with network size expansion. This paper explores a novel RMLSA, proposing a comprehensive solution addressing route determination and spectrum assignment concurrently. The necessity of concurrent resolution arises from the mutual interdependence between route determination and spectrum allocation. The optimization of overall performance is bolstered by the combination of mutual dependence and the formulation of an objective function that considers both spectrum utilization and fragmentation. So, an objective function has been developed and designated as ABA-CUS, Adaptive Balance of Average Clustering and Utilization of Spectrum. This nomenclature highlights the objective function's capability to adjust and assign significance to both “average clustering” (lower fragmentation) and “spectrum utilization”. Our approach involves formulating an Integer Linear Programming (ILP) model with a simple relationship between path and spectrum constraints. The simulation results shows the reduction in the resources utilized and the fragmentation along with the lowered bandwidth blocking probability at different arrival rates.