Title :
A P2P Traffic Identification Method Based on VFDT
Author :
Sun, Meifeng ; Zhang, Yun ; Chen, Jingtao ; Shi, Tingting
Author_Institution :
Inf. Eng. Coll., Yangzhou Univ., Yangzhou, China
Abstract :
We analyzed the memory limitation problem of traffic identification arithmetic when faced the large and fast stream data, and extracted the traffic attribute based on the P2P working mechanism. Using VFDT method to identify the P2P traffic can scan the traffic data only once relying on the Hoeffding Restriction, the method reduce the complexity of algorithm on the part of timing and memory and ensure the identification correction rate. The experiment shows the method can get good performance.
Keywords :
decision trees; learning (artificial intelligence); peer-to-peer computing; telecommunication traffic; Hoeffding restriction method; P2P traffic identification method; VFDT method; decision tree learning method; identification correction rate; traffic attribute extraction; traffic identification arithmetic; very fast decision tree method; Automation; Bandwidth; Data engineering; Decision trees; Machine learning; Machine learning algorithms; Statistics; Sun; Telecommunication traffic; Testing; Machine Learning; P2P Application; Traffic Identification;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
DOI :
10.1109/ICICTA.2010.90
