Data preprocessing for machine-learning-based adaptive data center transmission

To enable optical interconnect fluidity in next-generation data centers, we propose adaptive transmission based on machine learning a wavelength-routing network. We consider programmable transmitters that can apply N possible code rates to connections predicted bit error rate (BER) values. classify the BER, employ preprocessing algorithm feed traffic neural network classifier. demonstrate significance of our proposed and classifier performance for different values switch port count.