Location-Dependent Parameterization of a Random Direction Mobility Model

Abstract

Mobility models are widely used in simulation-based performance analyses of mobile networks. However, there is a trade-off between simplicity and realistic movement patterns. Synthetic models like the random waypoint and random direction model are simple to implement, but only provide unrealistic simple user sojourn densities and traffic flows. In contrast, graph and trip-based mobility models are complex to parameterize and their results are difficult to compare. In this paper, we propose the location-dependent parameterization of the random direction model to fill this gap. This model extension allows to setup non-homogeneous mobility scenarios, in particular based on real-world traces, while it still belongs to the class of synthetic random walk mobility models. We show that the location-dependent parametrization can accurately model arbitrary mobility patterns with very limited implementation complexity.