An optimisation model for traffic distribution forecasting in packet-switching networks
by Faramak Zandi, Madjid Tavana
International Journal of Mathematics in Operational Research (IJMOR), Vol. 2, No. 5, 2010

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.

Online publication date: Sun, 01-Aug-2010

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Mathematics in Operational Research (IJMOR):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com