Machine Learning-Based Traffic Prediction for Optical Switching Resource Allocation in Hybrid Intra-Data Center Networks

This work presents a highly accurate traffic prediction model based on nonlinear autoregressive neural networks for efficient forecasting of heavy traffic streams in intra-data center networks. Its deep-learning version guarantees a prediction error of 10
^-10
.