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Data Preprocessing for Machine-Learning-Based Adaptive Data Center Transmission
Kamran Keykhosravi,Ahad Hamednia,Houman Rastegarfar,Erik Agrell 한국통신학회 2022 ICT Express Vol.8 No.1
To enable optical interconnect fluidity in next-generation data centers, we propose adaptive transmission based on machine learning in a wavelength-routing network. We consider programmable transmitters that can apply possible code rates to connections based on predicted bit error rate (BER) values. To classify the BER, we employ a preprocessing algorithm to feed the traffic data to a neural network classifier. We demonstrate the significance of our proposed preprocessing algorithm and the classifier performance for different values of and switch port count.