The multi-source model for dimensioning data networks

Thomas Bonald, Céline Comte

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)


Traffic modeling is key to the dimensioning of data networks. Usual models rely on the implicit assumption that each user generates data flows in series, one after the other, the ongoing flows sharing equitably the considered network link. We relax this assumption and consider the more realistic case where users may generate several data flows in parallel, these flows having to share the user's access line as well. We qualify this model as multi-source since each user now behaves as an independent traffic source. Usual performance metrics like mean throughput and congestion rate must now be defined at user level rather than at flow level. We derive explicit expressions for these performance metrics under the assumption that flows share bandwidth according to balanced fairness. These results are compared with those obtained by simulation when max-min fairness is imposed, either at flow level or at user level.

Original languageEnglish
Pages (from-to)225-233
Number of pages9
JournalComputer Networks
Publication statusPublished - 9 Nov 2016
Externally publishedYes


  • Balanced fairness
  • Congestion rate
  • Flow-level model
  • Max-min fairness
  • Mean throughput


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