Over the last few years, peer-to-peer (P2P) applications have relentlessly grown
to represent a formidable component of Internet traffic. In contract to P2P networks
witch used well-defined port number, current P2P applications have use of arbitrary
ports. As P2P applications continue to evolve, robust and effective methods are
methods are needed for P2P traffic identification. Many P2P applications are
bandwidth-intensive. Understanding the Internet traffic profile is important for several
reasons, including traffic engineering, network service pricing.
In this Thesis, we integrated port-based method into original Classifier which is
using content-based method only. Therefore, we can improve the recognition rate for
Classifier and identify more applications. We also verified our Classifier recognition
rate by using the results of Service Control Engine.
Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0212108-165100 |
Date | 12 February 2008 |
Creators | Hsu, Yu-San |
Contributors | Ce-Kuen Shieh, Chu-Sing Yang, Chungnan Lee, Mon-Yen Luo, Chun-Hung Lin |
Publisher | NSYSU |
Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
Language | Cholon |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0212108-165100 |
Rights | withheld, Copyright information available at source archive |
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