Predictive networking and optimization for flow-based networks

TL;DR

This paper demonstrates that neural networks can accurately classify flow sizes in flow-based networks, enabling prioritized routing and efficient memory usage.

Contribution

It introduces a neural network-based method to predict flow sizes with high accuracy, aiding in network optimization.

Findings

Flow size prediction accuracy of 87% using ANN

Potential for improved flow prioritization in routers

Enhanced memory management through flow classification

Abstract

Artificial Neural Networks (ANNs) were used to classify neural network flows by flow size. After training the neural network was able to predict the size of a flows with 87% accuracy with a Feed Forward Neural Network. This demonstrates that flow based routers can prioritize candidate flows with a predicted large number of packets for priority insertion into hardware content-addressable memory.