  Opportunistic networks (OppNets) are focused to exploit direct, localised
communications which occur in a peer-to-peer manner mostly based on people's
movements and their contact durations. Therefore, the use of realistic mobility
models is critical to evaluate the data dissemination in OppNets. One of the
mobility models that is available in OMNeT++ which can be used to mimic human
movement patterns is Small Worlds in Motion (SWIM). The SWIM model is based on
the intuition that humans often visit nearby locations and if the visited
location is far away, then it is probably due to the popularity of the
location. As an alternative to mobility of a node, pairwise contact
probabilities are also used to evaluate the data dissemination in OppNets.
Pairwise contact probabilities can be used to predict that a node will be met
by a particular node. These probabilities can be derived in many ways. One of
the ways is to calculate the average probability with which a node will meet
another particular node at any point of time. Another way is to calculate the
probability with which a node will meet another based on the time of day. The
way of calculating pairwise contact probability depends on the scenario. In
this work, the pairwise contact probabilities obtained from the real traces are
used to tune the parameters of the SWIM mobility model. The traces and the SWIM
model are compared in terms of contact durations, inter-contact times and,
number of pairwise contacts. How to decide SWIM parameters using real contact
traces are being addressed.
