An early recognition algorithm for BitTorrent traffic based on improved K-means

In response to the deficiencies of BitTorrent, the concept of density radius was proposed, and the distance from the maximum point of radius density to cluster center as a cluster radius was taken to solve the too large cluster radius resulted from the discrete points and to reduce the false positiv...

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Bibliographic Details
Published in:Journal of Central South University of Technology. Science & technology of mining and metallurgy 2011-12, Vol.18 (6), p.2061-2067
Main Authors: Rong, Hui-gui, Li, Ming-wei, Cai, Li-jun
Format: Article
Language:English
Subjects:
Engineering
Metallic Materials
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Summary:In response to the deficiencies of BitTorrent, the concept of density radius was proposed, and the distance from the maximum point of radius density to cluster center as a cluster radius was taken to solve the too large cluster radius resulted from the discrete points and to reduce the false positive rate of early recognition algorithms. Simulation results show that in the actual network environment, the improved algorithm, compared with K-means, will reduce the false positive rate of early identification algorithm from 6.3% to 0.9% and has a higher operational efficiency.
ISSN:1005-9784
1993-0666
DOI:10.1007/s11771-011-0943-8