System and method to learn and prescribe network path for SDN

摘要

A path suggestion tool in a Software-Defined Networking (SDN) architecture to predict a router's future usage based on an analysis of the router's historical usage over a given period of time in the past and to recommend a routing path within the network in view of the predicted future usages of the routers/switches in the network. The path suggestion tool is an analytical, plug-and-play model usable as part of an SDN controller to provide more insights into different routing paths based on the future usage of each router. A Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) model in the suggestion tool analyzes the historical usage data of a router to predict its future usage. A Deep Boltzmann Machine (DBM) model in the suggestion tool recommends a routing path within the SDN-based network upon analysis of the LSTM-RNN based predicted future usages of routers/switches in the network.