  This paper investigates the performance of epidemic routing in mobile social
networks. It first analyzes the time taken for a node to meet the first node of
a set of nodes restricted to move in a specific subarea. Afterwards, a
monolithic Stochastic Reward Net (SRN) is proposed to evaluate the delivery
delay and the average number of transmissions under epidemic routing by
considering skewed location visiting preferences. This model is not scalable
enough, in terms of the number of nodes and frequently visited locations. In
order to achieve higher scalability, the folding technique is applied to the
monolithic model, and an approximate folded SRN is proposed to evaluate
performance of epidemic routing. Discrete-event simulation is used to validate
the proposed models. Both SRN models show high accuracy in predicting the
performance of epidemic routing. We also propose an Ordinary Differential
Equation (ODE) model for epidemic routing and compare it with the folded model.
Obtained results show that the folded model is more accurate than the ODE
model. Moreover, it is proved that the number of transmissions by the time of
delivery follows uniform distribution, in a general class of networks, where
positions of nodes are always independent and identically distributed.
