Predicting peer offline probability in BitTorrent using nonlinear regression

  • Dongdong Nie*
  • , Qinyong Ma
  • , Lizhuang Ma
  • , Wuzheng Tan
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

BitTorrent is a popular and scalable P2P content distribution tool. This study attempts to analyze the factors that affect the offline probability of BitTorrent peer, and express the probability using these factors. We first collect large data set of BitTorrent peers' activities. Then we use nonlinear least-squares regression to determine the probability distribution function for each of the three factors (download percent, download speed, and local time) and the joint probability distribution function of the three factors, and use another large data set to verify the prediction results.

Original languageEnglish
Title of host publicationEntertainment Computing - ICEC 2007 - 6th International Conference, Proceedings
EditorsLizhuang Ma, Matthias Rauterberg, Ryohei Nakatsu
PublisherSpringer Verlag
Pages339-344
Number of pages6
ISBN (Print)3540748725, 9783540748724
DOIs
StatePublished - 2007
Externally publishedYes
Event6th International Conference of Entertainment Computing, ICEC 2007 - Shanghai, China
Duration: 15 Sep 200717 Sep 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4740 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference of Entertainment Computing, ICEC 2007
Country/TerritoryChina
CityShanghai
Period15/09/0717/09/07

Keywords

  • Bittorrent
  • Offline
  • Probability distribution
  • Regression

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