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Measurement and analysis of P2P IPTV program resource.

Wenxian Wang1, Xingshu Chen2, Haizhou Wang2

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Researchers developed a P2P IPTV crawler, collecting 13 million program resources. Analysis revealed chaotic program names, hindering retrieval, and proposed a hot program model for popularity prediction.

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Area of Science:

  • Computer Science
  • Information Science

Background:

  • Peer-to-peer (P2P) technology is rapidly advancing, increasing the relevance of P2P Internet Protocol Television (IPTV) applications.
  • Effective program resource distribution is crucial for the performance of P2P IPTV services.

Purpose of the Study:

  • To address the challenge of collecting and organizing P2P IPTV program resources.
  • To analyze the characteristics of P2P IPTV program resources, focusing on naming conventions.
  • To develop a model for predicting program popularity and user behavior.

Main Methods:

  • A distributed multi-protocol crawler was designed and implemented to collect IPTV program data.
  • Collected over 13 million IPTV program entries from 2009 to 2012.
  • Performed characteristic analysis on program names, including length distribution, character type entropy, and hierarchy depth.

Main Results:

  • The study identified chaotic and disorganized naming conventions in P2P IPTV programs.
  • Analysis revealed issues with program name length, character variety, and hierarchical structure.
  • An analytical model for hot programs was proposed to represent popularity and predict user behavior.

Conclusions:

  • The findings highlight the need for better organization and purification of P2P IPTV program data.
  • The analysis provides insights to improve program retrieval, automatic sorting, and repository establishment.
  • The hot program model offers a method for understanding program popularity dynamics.