A Markovian Waypoint Mobility Model with Application to Hotspot Modeling

In this paper we introduce a Markovian random waypoint model which allows us to create diverse mobility patterns in the given movement domain. The model allows adjusting random pause times and the momentary velocity. Furthermore, the distribution used to pick the next waypoint may depend on the current location, which allows, e.g., creation of typical routes. As an application for the Markovian random waypoint we consider modelling hotspots. There are several mechanisms which may be causing a hotspot and we present how the parameters of the proposed model can be adjusted accordingly to match the scenario in question. We further illustrate how two seemingly similar mobility patterns lead to highly different estimates of achievable performance levels. Finally, we show how the state of the MWP model can be initialised in simulations such that the node starts from the stationary state without any initial transient.