NeuRoute: Predictive Dynamic Routing for Software-Defined Networks

TL;DR

NeuRoute is a machine learning-based dynamic routing framework for SDN that predicts traffic in real time and generates forwarding rules to optimize throughput efficiently.

Contribution

It introduces a neural network-based, controller-agnostic routing framework that predicts traffic and optimizes network throughput faster than existing heuristics.

Findings

Achieves comparable throughput to the best heuristics

Reduces execution time for routing decisions

Operates independently of specific SDN controllers

Abstract

This paper introduces NeuRoute, a dynamic routing framework for Software Defined Networks (SDN) entirely based on machine learning, specifically, Neural Networks. Current SDN/OpenFlow controllers use a default routing based on Dijkstra algorithm for shortest paths, and provide APIs to develop custom routing applications. NeuRoute is a controller-agnostic dynamic routing framework that (i) predicts traffic matrix in real time, (ii) uses a neural network to learn traffic characteristics and (iii) generates forwarding rules accordingly to optimize the network throughput. NeuRoute achieves the same results as the most efficient dynamic routing heuristic but in much less execution time.