Predicting Large-Scale WLAN Traffic via Granger Causality Based Bayesian Network

Abstract

Granger causality existed between traffic at different access points of large-scale wireless LANs was discovered.The Granger causality illustrates that the historical traffic of access points that exist causality within target access points help predict the future of target access points with better accuracy than when considering information from the past of target access point alone.Bayesian network to model the causal relationship between access points and adopted a Gaussian mixture model（GMM）was used，as well as a weighted combination of several normal distribution functions in order to approximate the joint probability distribution in Bayesian networks.Finally，the traffic data in large-scale wireless LANs was imported，having hundreds of access points，to verify the accuracy of the proposed method，and a processing flow of analysis，modeling and prediction of traffic flow data was established.

Keywords

• WLAN
• traffic prediction
• traffic characteristics
• Granger causality
• Bayesian network