SVM-based analysis and prediction on network traffic
- 10.2991/iske.2007.284How to use a DOI?
- Network traffic, Predictive model, LS-SVM, NS2
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
- © 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/).
Cite this article
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 -