SVM-based analysis and prediction on network traffic

DOI

10.2991/iske.2007.284How to use a DOI?

Keywords

Network traffic, Predictive model, LS-SVM, NS2

Abstract

With continuous scale-up of the network and increase of the kinds of the services on the network, more and more people pay attention to the modeling and prediction for network traffic. Recently, SVM (Support Vector Machine), a new machine learning method, is comprehensively used to solve the problem of non-liner classification and regression. A network traffic predictive method presented in this paper is based on the LS-SVM (Least Squares SVM). Using NS2 simulator, we simulate the process of the network running with Drop-tail and RED controller respectively, then collect the being predicted traffic data which is on the bottleneck router. The results on the precision of prediction is good and feasible

Copyright

© 2007, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Weidong Luo
AU  - Xingwei Liu
AU  - Jian Zhang
PY  - 2007/10
DA  - 2007/10
TI  - SVM-based analysis and prediction on network traffic
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 1657
EP  - 1660
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.284
DO  - 10.2991/iske.2007.284
ID  - Luo2007/10
ER  -