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

Analysis of Spatio-Temporal Preferences and Encounter Statistics for DTN Performance