• DocumentCode
    3846921
  • Title

    Power Law and Exponential Decay of Intercontact Times between Mobile Devices

  • Author

    Thomas Karagiannis;Jean-Yves Le Boudec;Milan Vojnovic

  • Author_Institution
    Microsoft Research, Cambridge, UK
  • Volume
    9
  • Issue
    10
  • fYear
    2010
  • Firstpage
    1377
  • Lastpage
    1390
  • Abstract
    We examine the fundamental properties that determine the basic performance metrics for opportunistic communications. We first consider the distribution of intercontact times between mobile devices. Using a diverse set of measured mobility traces, we find as an invariant property that there is a characteristic time, order of half a day, beyond which the distribution decays exponentially. Up to this value, the distribution in many cases follows a power law, as shown in recent work. This power law finding was previously used to support the hypothesis that intercontact time has a power law tail, and that common mobility models are not adequate. However, we observe that the timescale of interest for opportunistic forwarding may be of the same order as the characteristic time, and thus, the exponential tail is important. We further show that already simple models such as random walk and random waypoint can exhibit the same dichotomy in the distribution of intercontact time as in empirical traces. Finally, we perform an extensive analysis of several properties of human mobility patterns across several dimensions, and we present empirical evidence that the return time of a mobile device to its favorite location site may already explain the observed dichotomy. Our findings suggest that existing results on the performance of forwarding schemes based on power law tails might be overly pessimistic.
  • Keywords
    "Tail","Humans","Protocols","Mobile communication","Time measurement","Pattern analysis","Performance analysis","Distribution functions","Probability distribution","Delay effects"
  • Journal_Title
    IEEE Transactions on Mobile Computing
  • Publisher
    ieee
  • ISSN
    1536-1233
  • Type

    jour

  • DOI
    10.1109/TMC.2010.99
  • Filename
    5473233