Applications of Artificial Intelligence, Machine Learning and related techniques for Computer Networking Systems

TL;DR

This paper provides an overview of how AI and ML techniques are applied to various computer networking problems, including traffic management, security, and fault diagnosis, highlighting datasets, tools, and standards involved.

Contribution

It offers a comprehensive summary of AI/ML applications in networking, including techniques, datasets, tools, and standards, emphasizing recent successful implementations.

Findings

AI/ML improve traffic prediction and classification accuracy

Enhanced network security and anomaly detection using AI/ML

Effective network resource optimization with machine learning

Abstract

This article presents a primer/overview of applications of Artificial Intelligence and Machine Learning (AI/ML) techniques to address problems in the domain of computer networking. In particular, the techniques have been used to support efficient and accurate traffic prediction, traffic classification, anomaly detection, network management, network security, network resource allocation and optimization, network scheduling algorithms, fault diagnosis and many more such applications. The article first summarizes some of the key networking concepts and a few representative machine learning techniques and algorithms. The article then presents details regarding the availability of data sets for networking applications and machine learning software and toolkits for processing these data sets. Highlights of some of the standards activities, pursued by ITU-T and ETSI, which are related to AI/ML for networking, are also presented. Finally, the article discusses a small set of representative networking problems where AI/ML techniques have been successfully applied.