P2PTV traffic localization by deep packet inspection

Hiep Hoang-Van, Takumi Miyoshi, Olivier Fourmaux

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recently, peer-to-peer has been becoming a promising architecture for developing video streaming services because it can reduce the bottlenecks and the load at the server side. However, P2P systems implement their own routing protocols on overlay networks, which are largely independent of the Internet routing. As a result, the traffic generated by P2P systems is immense and unpredictable. Controlling the P2P traffic is therefore becoming a big challenge for internet service providers (ISPs). Considering the P2P traffic localization is one of the most efficient solutions to optimize the traffic. The existing approaches, however, require several modifications of the application software. In this paper, we propose a novel traffic localization method for P2P streaming application (P2PTV) by deep packet inspection. Based on the peer list and the geographical location of the listed peers, we propose two mechanisms for localizing the traffic: the modification of the peer list packets and the redirection of the video request packets at network routers. Since our method is implemented on the network routers, it can be applied for all P2P applications without any software modifications. The experiments evaluated on a popular P2PTV, namely PPStream, prove the effectiveness of our proposed method on the problem of traffic localization.

Original languageEnglish
Title of host publicationSNPD 2013 - 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
Pages375-380
Number of pages6
DOIs
Publication statusPublished - 2013
Event14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2013 - Honolulu, HI
Duration: 2013 Jul 12013 Jul 3

Other

Other14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2013
CityHonolulu, HI
Period13/7/113/7/3

Fingerprint

Routers
Inspection
Internet service providers
Overlay networks
Video streaming
Routing protocols
Application programs
Computer systems
Servers
Internet
Experiments

Keywords

  • P2PTV
  • Peer list
  • Traffic localization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

Cite this

Hoang-Van, H., Miyoshi, T., & Fourmaux, O. (2013). P2PTV traffic localization by deep packet inspection. In SNPD 2013 - 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (pp. 375-380). [6598491] https://doi.org/10.1109/SNPD.2013.77

P2PTV traffic localization by deep packet inspection. / Hoang-Van, Hiep; Miyoshi, Takumi; Fourmaux, Olivier.

SNPD 2013 - 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. 2013. p. 375-380 6598491.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hoang-Van, H, Miyoshi, T & Fourmaux, O 2013, P2PTV traffic localization by deep packet inspection. in SNPD 2013 - 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing., 6598491, pp. 375-380, 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2013, Honolulu, HI, 13/7/1. https://doi.org/10.1109/SNPD.2013.77
Hoang-Van H, Miyoshi T, Fourmaux O. P2PTV traffic localization by deep packet inspection. In SNPD 2013 - 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. 2013. p. 375-380. 6598491 https://doi.org/10.1109/SNPD.2013.77
Hoang-Van, Hiep ; Miyoshi, Takumi ; Fourmaux, Olivier. / P2PTV traffic localization by deep packet inspection. SNPD 2013 - 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. 2013. pp. 375-380
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