Capturing Internet Traffic Dynamics through Graph Distances

  • Steve Uhlig
  • Bingjie Fu
  • Almerima Jamakovic
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 5)


Studies of the Internet have typically focused either on the routing system, i.e. the paths chosen to reach a given destination, or on the evolution of traffic on a physical link. In this paper, we combine routing and traffic, and study for the first time the evolution of the traffic on the Internet topology. We rely on the traffic and routing data of a large transit provider, spanning almost a month.

We compute distances between the traffic graph over small and large timescales. We find that the global traffic distribution on the AS graph largely differs from traffic observed at small timescales. However, variations between consecutive time periods are relatively limited, i.e. the topology spanned by the traffic from one time period to the next is small. This difference between local and global traffic distribution is found in the timescales at which traffic dynamics occurs on AS-level links. Small timescales, i.e. less than a few hours, do not account for a significant fraction of the traffic dynamics. Most of the traffic variability is concentrated at timescales of days. Models of Internet traffic on its topology should thus focus on capturing the long-term changes in the global traffic pattern.


Internet traffic AS topology graph distance multi-resolution analysis 


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Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2009

Authors and Affiliations

  • Steve Uhlig
    • 1
  • Bingjie Fu
    • 2
  • Almerima Jamakovic
    • 3
  1. 1.TU Berlin/Deutsche Telekom labsBerlinGermany
  2. 2.Delft University of TechnologyDelftNetherlands
  3. 3.TNO ICTDelftNetherlands

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