Mobility models studied in the networking community usually assume independence between the movement of individuals. While this may well model sparse networks, there are many scenarios that might not follow this assumption. In contrast, within other communities, such as road traffic engineering, biology and computer graphics, models of mobility usually take into account the dependence of the mobility pattern of an individual with respect to that of its neighbors. Our goal in this paper is to study how this dependence impacts the performance measure from the networking point of view. In particular, we implement a bio-inspired model for mobility of crowds and, by simulation, we study how mobility influences the performance measures of a distributed network. We perform statistical analysis on the samples obtained through simulations. In particular, we study the distribution of the message delivery time and show that it is light tailed, with exponential tail distribution.