A fluid background traffic model

  • Authors:
  • Ting Li;Jason Liu

  • Affiliations:
  • School of Computing and Information Sciences, Florida International University;School of Computing and Information Sciences, Florida International University

  • Venue:
  • ICC'09 Proceedings of the 2009 IEEE international conference on Communications
  • Year:
  • 2009

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Abstract

Background traffic has a significant impact on the behavior of network services and protocols. However, a detailed model of the background traffic can be extremely time consuming in simulation. In this paper, we extend our previous hybrid model that combines fluid and packet-oriented characterization of network traffic for a realistic representation of the background traffic on Internet. In particular, we get rid of some unrealistic assumptions in the hybrid model, by adding an acknowledgment scheme to correctly capture the mutual influence of fluid TCP flows on network queues, and by applying the Poisson Pareto Burst Process (PPBP) model to describe the long-range dependencies of the Internet traffic. Experiments show that our fluid background traffic model can capture similar level of realism as the traditional packet-oriented approach.