Geo-CoMM: A geo-community based mobility model

Abstract

The paper proposes a new mobility model able to properly reproduce the spatial, temporal and social features that can be observed in real mobility datasets. The model, named Geo-CoMM, is based on the quantities that guide human mobility and their probability distributions by directly extracting their setting from the statistical analysis of GPS-based traces. In Geo-CoMM, people move within a set of geo-communities, i.e. locations loosely shared among people, following speed, pause time and choice rules whose distribution is obtained by the statistical analysis; similarly, inside a geo-community, people move according to a Lévy walk. The paper also introduces a methodology to derive social relationships from traces, by representing the system (node, geocommunity) as a bipartite graph whose projections on nodes indicate the strength of the relationships amongst nodes. Finally, simulation results are presented to show how the model correctly reproduces all the statistics of some real trace datasets through a simple setting of environment parameters.