Author(s):
Geza Szabo, Daniel Orincsay,Balazs, Peter Gero, Sandor Gyori, Tamas Borsos
Wireless Internet Conference, 2007, Austin, Texas, USA
Download document:
Traffic Analysis of Mobile Broadband Networks (pdf)
Abstract:
Detailed knowledge about the traffic mixture is essential for network operators and administrators, as it is a key input for numerous network management activities. Basically, traffic analysis aims at identifying the traffic mixture of the network. Several different approaches co-exist in the literature, but none of them performs well for all different application traffic types present in the Internet. Therefore, one approach is to combine the advantages of different identification methods, in order to improve the completeness and accuracy of classification. In this study we compare and benchmark the currently known traffic classification methods on network traces captured in an operational 3G mobile network. Utilizing the experiences about the strengths and weaknesses of the existing approaches, a novel traffic classification method is proposed. The novel method is based on a complex decision mechanism, in order to provide appropriate identification for each different application type. As main result, the ratio of the unclassified traffic becomes significantly lower. Further, the reliability of the classification improves, as the various methods validate the results of each other. The novel method is tested on passive measurements of an operational mobile broadband network, and it is presented how the proposed solution improves traffic classification, when compared to existing methods. As a main contribution, it is shown that applications previously used only in fixed access networks may appear in mobile broadband environment.
Notice:
Copyright 2002 IEEE. Reprinted from Taipei, November, 2002. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Ericsson's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
In order to read PDF files, you need to have Adobe® Acrobat® Reader® installed in your computer. You can download the latest Acrobat® Reader® for free from Adobe's website.
