A Review of Network Traffic Analysis and Prediction Techniques

TL;DR

This survey reviews diverse techniques for analyzing and predicting network traffic, highlighting their applications in enhancing security and reliability in computer networks.

Contribution

It provides a comprehensive overview of existing methods and investigates the rules and uniqueness of prior studies in network traffic analysis and prediction.

Findings

Neural network and data mining techniques are used for analysis.

Linear and non-linear models are applied for prediction.

Various combinations of techniques improve efficiency.

Abstract

Analysis and prediction of network traffic has applications in wide comprehensive set of areas and has newly attracted significant number of studies. Different kinds of experiments are conducted and summarized to identify various problems in existing computer network applications. Network traffic analysis and prediction is a proactive approach to ensure secure, reliable and qualitative network communication. Various techniques are proposed and experimented for analyzing network traffic including neural network based techniques to data mining techniques. Similarly, various Linear and non-linear models are proposed for network traffic prediction. Several interesting combinations of network analysis and prediction techniques are implemented to attain efficient and effective results. This paper presents a survey on various such network analysis and traffic prediction techniques. The uniqueness and rules of previous studies are investigated. Moreover, various accomplished areas of analysis and prediction of network traffic have been summed.