  Spatio-temporal preferences and encounter statistics provide realistic
measures to understand mobile user's behavioral preferences and transfer
opportunities in Delay Tolerant Networks (DTNs). The time dependent behavior
and periodic reappearances at specific locations can approximate future online
presence while encounter statistics can aid to forward the routing decisions.
It is theoretically shown that such characteristics heavily affect the
performance of routing protocols. Therefore, mobility models demonstrating such
characteristics are also expected to show identical routing performance.
However, we argue models despite capturing these properties deviate from their
expected routing performance. We use realistic traces to validate this
observation on two mobility models. Our empirical results for epidemic routing
show those models' largely differ (delay 67% & reachability 79%) from the
observed values. This in-turn call for two important activities: (i) Analogous
to routing, explore structural properties on a Global scale (ii) Design new
mobility models that capture them.
