DocumentCode :
1806693
Title :
Traffic classification using cost based decision tree
Author :
Wang, Lin ; Zhou, Xuan ; Gu, Rentao
Author_Institution :
Sch. of Inf. & Commun., Beijing Univ. of Posts & Telecommun.(BUPT), Beijing, China
Volume :
4
fYear :
2011
fDate :
24-26 Dec. 2011
Firstpage :
2545
Lastpage :
2550
Abstract :
A novel method for achieving practical real-time traffic classification is proposed in this paper, which is based on C4.5 decision tree. Most existing traffic classification algorithms only focus on accuracy of the classification results, but lack of considering the various costs in actual deployment. So they cannot guarantee that the obtained tree construction is optimal for hardware and software processing. To solve this problem, our Cost Based Feature Evaluation procedure defines UnitGainRatio as the metric of attributes to find the best tree construction when considering the attribute acquisition and processing cost. We also introduce another method called Fuzzy Delicacy Node Selection procedure to choose the more suitable node, when their UnitGainRatio are too close to each other. The experiment results show that the proposed method reduces the average cost compared with similar algorithm.
Keywords :
Internet; decision trees; feature extraction; fuzzy set theory; pattern classification; C4.5 decision tree; UnitGainRatio; attribute acquisition; attribute metric; cost based feature evaluation; fuzzy delicacy node selection procedure; processing cost; real-time traffic classification; tree construction; Computer networks; decision tree; machine learning; traffic classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2011 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-1586-0
Type :
conf
DOI :
10.1109/ICCSNT.2011.6182488
Filename :
6182488
Link To Document :
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