EPFIA: Extensible P2P Flows Identification Architecture


The fundament of managing P2P traffic is identifying various P2P flows accurately. Although many P2P flows identification methods are presented nowadays, there are no ideas for either integrating these independent methods together or being extended fast to support new method. In this work, an extensible P2P flows identification architecture (EPFIA for short) is proposed. In order to identify many specific P2P flows, EPFIA uses many different identification methods simultaneously, and obtains the highest efficiency via adjusting their identification sequence. An online mechanism of renewing identification methods is designed, which can extend new identification method without compiling the whole program. Applying policy mechanism, identification methods can be updated, started and halted remotely. The experiment results of running the prototype system show us that EPFIA could effectively promote the performance of system and support online renew P2P identification methods and manage them remotely.

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Xu, B. , Li, B. , Hu, C. and Zhang, G. (2013) EPFIA: Extensible P2P Flows Identification Architecture. Journal of Applied Mathematics and Physics, 1, 56-62. doi: 10.4236/jamp.2013.14011.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] H. Schulze and K. Mochalski, “Internet Study 2008/2009,” Technical Report, Ipoque GmbH, 2009.
[2] K. C. Claffy, “Internet Traffic Characterization,” University of California, San Diego, 1994.
[3] T. Karagiannis and A. Broido, “Is P2P Dying or Just Hiding?” IEEE GLOBECOM 2004, Dallas, Texas, 29 November-3 December 2004, pp. 1532-1538.
[4] S. Sen and O. Spatscheck, “Accurate, Scalable In-Network Identification of P2P Traffic Using Application Signatures,” WWW2005, New York, USA, 17-22 May 2004, pp. 512-521.
[5] M. Roughan and S. Sen, “Class-of-Service Mapping for QoS: A Statistical Signature-Based Approach to IP Traffic Classification,” IMC 2004, Taormina, Italy, 25-27 October 2004, pp. 135-148.
[6] A. Moore and K. Papagiannaki, “Toward the Accurate Identification of Network Applications,” PAM 2005, Boston, USA, 31 March-1 April 2005.
[7] T. Karagiannis and A. Broido, “Transport Layer Identification of P2P Traffic,” In IMC’04, Taormina, Italy, 25-27 October 2004, 14p.
[8] T. Karagiannis and K. Papagiannaki, “BLINK: Multilevel Traffic Classification in the Dark,” SIGCOMM’05, Philadelphia, USA, 21-26 August 2005, 12p.
[9] L. Bernaille and R. Teixeira, “Early Application Identification,” The 2nd ADETTI/ISCTE CoNEXT Conference, Lisboa, Portugal, December 2006.
[10] M. Crotti and M. Dusi, “Traffic Classification through Simple Statistical Fingerprinting,” SIGCOMM Computer Communication Review, Vol. 37, No. 1, 2007, pp. 5-16. http://dx.doi.org/10.1145/1198255.1198257

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