DocumentCode
588934
Title
An Improved Classification Method of Unstructured P2P Multicast Video Streaming
Author
Chaobin Liu ; Qiang Guo ; Jie He
Author_Institution
Inf. Center, Second Mil. Med. Univ., Shanghai, China
Volume
2
fYear
2012
fDate
28-29 Oct. 2012
Firstpage
415
Lastpage
418
Abstract
The classification of unstructured P2P multicast video streaming is the premise for playing online linkage and real-time evidence in the process of network monitoring management. Based on the classification method in the preliminary research, an improved classification method is proposed. the method uses an optimal feature vector extraction algorithm to filter the proposed behavior features in the original method, which greatly lower the feature vector dimension. an improved multi-class support vector machines is also used in the improved method, which not only solves the problem of rejecting sub-regional, but also reduces the computational complexity and improves the identification accuracy. Experiments show that the improved method has less computational and storage overhead, and has higher identification accuracy.
Keywords
computational complexity; multicast communication; peer-to-peer computing; support vector machines; video streaming; classification method; computational complexity; multiclass support vector machines; network monitoring management; online linkage; optimal feature vector extraction algorithm; real-time evidence; unstructured P2P multicast video streaming; Accuracy; Binary trees; Feature extraction; Streaming media; Support vector machine classification; Vectors; classification; improved method; unstructured P2P multicast video streaming;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
Conference_Location
Hangzhou
Print_ISBN
978-1-4673-2646-9
Type
conf
DOI
10.1109/ISCID.2012.259
Filename
6406027
Link To Document