Mobility modeling is a critical step in the design of mobile self-organizing networks. With the emergence of small-scale and short-range wireless communication devices, the communication sphere shrinks (radio range or sensing range), which leads to an increase in the need for fine-grained representations of mobility. In fact, mobility models must scale accordingly to the application and reflect real scenarios in which wireless devices are deployed. Currently, self-organizing networks are evaluated using mobility models that do not represent the precise motion of mobile individuals at small scales. In this article we present a new class of mobility models, namely, behavioral mobility (BM) models, which decomposes mobility into simple atomic individual behaviors. Combined, these behaviors yield realistic displacement patterns by reproducing the mobility observed at small scales in every day life, in both space and time.