Prediction of internet traffic based on Elman neural network

Authors:
Wang Junsong;Wang Jiukun;Zeng Maohua;Wang Junjie
Affiliations:
Tianjin University of Technology and Education, Tianjin;Dagang Oil Field, Tianjin;Dagang Oil Field, Tianjin;Dagang Oil Field, Tianjin
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Year:
2009

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Abstract

Predicting internet traffic is needed for effective dynamic bandwidth allocation and for quality-of-service (QoS) control strategies implemented at the network edges. In this paper, a method is presented to model and predict the internet traffic based on Elman neural network(Elman-NN). The traffic is viewed as a time series, which is nonlinear and variant functions. An Elman neural network is employed to model the relationship with a satisfactory accuracy, and the Elman NN-based traffic model is used to conduct prediction for the future traffic. The simulation results show that this method is feasible and efficient to model and predict the traffic.