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

Volume

1

fYear

2010

fDate

11-12 May 2010

Firstpage

281

Lastpage

284

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICICTA.2010.90

Filename

5523264