Fitting Opportunistic Network Data with a Pareto Distribution

We contrast properties and parameters of a Pareto distribution law with the behavior of memory endowed processes underlying the intercontact times of opportunistic networks. Within a general model where mobile agents meet together as a consequence of a common goal they are carrying out, the memory of the process identifies with the agent intention versus a goal, where intention consists in turn in the introduction of asymmetries into a random walk. With these elementary hypotheses we come to a very elementary agents mobility model as a semantic counterpart of the Pareto law. In particular this model gives a suitable meaning to law parameters and a rationale to its fitting of a benchmark of real intercontact times.