Machine Learning Methods for Traffic Prediction in Dynamic Optical Networks with Service Chains

Knowledge about future traffic in a dynamic optical network can be used to improve various performance metrics, including network cost and to reduce complexity of solving network optimization problems. In this paper, we propose a machine learning approach of predicting demands in a dynamic optical network serving Virtual Network Function (VNF) chain traffic. We also present numerical results proving effectiveness of the described methodology and...