Is P2P dying or just hiding? [P2P traffic measurement]

By Thomas Karagiannis, Andre Broido, N. Brownlee, K. Claffy, Michalis Faloutsos. IEEE Global Telecommunications Conference, 2004. GLOBECOM '04., 2004

544 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/cfd5cc87600f77112c6d75416585d596353ec920

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Citations in the corpus

Clustering and sharing incentives in BitTorrent systems (2006, background): “In just a few years, peer-to-peer content distribution has come to generate a significant portion of the total Internet traffic [ 14 ].”
On dominant characteristics of residential broadband internet traffic (2009, background): “In 2004 Karagiannis et al. [ 26 ] found P2P traffic increasingly moving away from well-known ports to dynamically negotiated ports.”
Understanding churn in peer-to-peer networks (2006, background): “Difficulties in correctly identifying peer-to-peer flows [ 12 ] can also limit measurement accuracy.”
A Survey on Internet Traffic Identification (2009, background): “It is already widely accepted that the use of well-known ports on its own to identify applications is obsolete [ 8 ][9][10][11].”
File Sharing: Creative Destruction or Just Plain Destruction?* (2006, background): “Some have argued that the lawsuits have had virtually no impact (Karagiannis et al. 2004).”
The Effect of Internet Piracy on Cd Sales: Cross-Section Evidence (2004, background): “13Contrary to the numbers presented in Table 2, Karagiannis et al. (2004) found that the”
BLINC: multilevel traffic classification in the dark (2005, methodology): “Payload-based classification approaches tailored to p2p trac have been presented in [19, 9 ], while identification of p2p trac through transport layer characteristics is proposed in [8].”
A survey of techniques for internet traffic classification using machine learning (2008, background): “However, many applications are increasingly using unpredictable (or at least obscure) port numbers [ 6 ].”
The Effect of File Sharing on Record Sales: An Empirical Analysis (2007, unknown): “U.S. households swap more than 300 million files each month, a figure that has grown by over 50 percent in the last two years (Karagiannis et al. 2004; Billboard 2006).”
A comprehensive survey on machine learning for networking: evolution, applications and research opportunities (2018, background): “Furthermore, relying solely on port numbers has been shown to be ineffective [125, 228, 320], largely due to the use of dynamic port negotiation, tunneling and misuse of port numbers assigned to well-known applications for obfuscating traffic and avoiding firewalls [54, 109, 176, 286].”
Early application identification (2006, background): “As a result, the applicability of port-based analysis is increasingly limited [ 15 , 23, 19, 16].”
Can ISPS and P2P users cooperate for improved performance? (2007, background): “P2P systems are so popular that they contribute more than 50% to the overall network traffic [ 3 , 4, 5].”
File Sharing and Copyright (2010, methodology): “Karagiannis et al. (2004) employ a similar methodology in studying Tier 1 ISP traffic.”
Rarest first and choke algorithms are enough (2006, methodology): “In a few years, peer-to-peer flle sharing has become the most popular application in the Internet [ 16 ,17].”
The Bittorrent P2P File-Sharing System: Measurements and Analysis (2005, methodology): “Measurements on Internet backbones indicate that BitTorrent has evolved into one of the most popular networks [ 8 ].”