Abstract
Metro network operators aim to design scalable and cost-effective network architectures to address the capacity expansion due to ongoing traffic growth. While coherent transmission (e.g., at 100 Gbps and 200 Gbps) can address capacity growth, operators must also support legacy non-coherent transmission technology (e.g., at 10 Gbps). Therefore, operators must devise new practical solutions to jointly support new and legacy transmission technologies, while minimizing the network cost. This study investigated the optimization problem arising when deploying a metro network with a hierarchical architecture of grooming nodes. More precisely, we optimized the deployment cost of hierarchical traffic-grooming stacked optical transport network (OTN) boards with a mix of coherent and non-coherent transmission technologies in metro/regional networks composed of interconnected rings, while considering a filterless node architecture. We formulated the optimization problem using integer linear programming. Then, to deal with problem scalability, we proposed a comprehensive set of novel heuristic approaches based on genetic algorithms, simulated annealing, and a knowledge-domain heuristic (local search). We also compared the proposed approaches with baseline strategies used by network operators and showed that we can reach up to 50% cost savings compared to these baselines.
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