Empirical modeling of campus-wide pedestrian mobility observations on the USC campus

Mobility is one of the main factors affecting the performance of ad hoc networks. Obtaining realistic mobility models is essential for the proper evaluation of ad hoc protocol performance. In our paper, we develop a hybrid mobility model, by observing the actual movement patterns of people on-campus and then post processing the data to form their spatio-temporal distributions. Our model differs from the synthetic and wireless network trace based models in that the model is empirical in nature and devoid of the restrictions as observed in some of the existing mobility models. Our model has been implemented by a structure similar to that of a finite state machine (FSM), using a tool that operates on our traces to generate another trace file which is readable by the network simulator (NS-2).