Date Added: Apr 2010
The complexity of social mobile networks (networks of devices carried by humans - e.g. sensors or PDAs - and communicating with short-range wireless technology) makes protocol evaluation hard. A simple and efficient mobility model such as SWIM reflects correctly kernel properties of human movement and, at the same time, allows to evaluate accurately protocols in this context. In this paper, the authors investigate the properties of SWIM, in particular how SWIM is able to generate social behavior among the nodes and how SWIM is able to model networks with a power-law exponential decay dichotomy of inter contact time and with complex sub-structures (communities) as the ones observed in the real data traces.