• DocumentCode
    2608884
  • Title

    P2P flows identification method based on listening port

  • Author

    Bo, Xu ; Ming, Chen ; Fei, Lan ; Na, Wang

  • Author_Institution
    Inst. of Command Autom., PLA Univ. of Sci. & Technol., Nanjing, China
  • fYear
    2009
  • fDate
    18-20 Oct. 2009
  • Firstpage
    296
  • Lastpage
    300
  • Abstract
    It is important to identify P2P flows accurately for effective network planning and design, security insuring, network management, network behavior understanding and so on. Firstly, an algorithm for identifying listening port of P2P host (LPIA for short) is proposed. Secondly, a heuristic algorithm of P2P flow identification (PFIA for short) is presented, which combines P2P host´s listening port, flow duration, flow length, the relationship of negotiation flow and data flow between different peers. And then a distributed P2P flows identification system (DPFIS) is introduced. DPFIS decentralizes LPIA and PFIA on different PC as well as NetFlow is used for flow clustering, which reduce the complexity for identifying P2P flows in high speed network. Finally, the algorithms are applied in campus network. Results show that our algorithms are simple and could recognize more kinds of P2P flows efficiently.
  • Keywords
    pattern clustering; peer-to-peer computing; telecommunication traffic; NetFlow; campus network; distributed P2P flow identification system; flow clustering; heuristic algorithm; high speed network; listening port; network behavior understanding; network management; network planning; security insuring; traffic flow; Bandwidth; Clustering algorithms; Communication system traffic control; Costs; Information filtering; Information filters; Internet; Network servers; Payloads; Telecommunication traffic; NetFlow; P2P; flow identification; listening port;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Broadband Network & Multimedia Technology, 2009. IC-BNMT '09. 2nd IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-4590-5
  • Electronic_ISBN
    978-1-4244-4591-2
  • Type

    conf

  • DOI
    10.1109/ICBNMT.2009.5348496
  • Filename
    5348496