Our Paper “Deep Learning Models For Aggregated Network Traffic Prediction” has been accepteed at IEEE/IFIP International Conference on Network and Service Management (CNSM 2019), 2019. This paper proposes framework leverages link statistics that can be easily collected either by the controller of a Software Defined Network (SDN), or by SNMP measurements in a legacy network, in order to predict future link throughputs.
