Title: An optimisation model for traffic distribution forecasting in packet-switching networks

Authors: Faramak Zandi, Madjid Tavana

Addresses: Faculty of Technology and Engineering, Alzahra University, Vanak, Tehran 19938-91176, Iran. ' Lindback Distinguished Chair of Information Systems, La Salle University, Philadelphia, PA 19141, USA

Abstract: Traffic distribution forecasting is an essential step in network planning for packet-switching networks. It is frequently necessary to forecast and develop an optimal network configuration to meet the requirements of new traffic demands or changes in the existing demands. Several methods have been developed to forecast network configurations. While these studies have revealed some interesting traffic characteristics, little progress has been made in developing good models for the purpose of traffic engineering and performance prediction. We propose a novel multi-objective optimisation model for traffic distribution forecasting in packet-switching networks by mapping these networks into multi-commodity networks. Initially, the radial basis function (RBF) network is used to monitor and learn the current real-traffic distribution. Next, a quadratic model is used to calibrate these functions for a precise traffic distribution. The proposed multi-objective optimisation method can effectively and efficiently forecast the traffic distribution of packet-switching networks in both crisp and fuzzy environments. A numerical example is presented to demonstrate the application and effectiveness of this model.

Keywords: fuzzy logic; multi-objective optimisation; RBF neural networks; multi-commodity networks; traffic distribution matrix; modelling; traffic distribution forecasting; packet switching networks; network configuration.

DOI: 10.1504/IJMOR.2010.034339

International Journal of Mathematics in Operational Research, 2010 Vol.2 No.5, pp.515 - 539

Published online: 01 Aug 2010 *

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