Perfect Simulations for Random Trip Mobility Models

The random trip model was recently proposed as a generic mobility model that contains many particular mo-bility models, including the widely-known random waypoint and random walks, and accommodates more realistic sce-narios. The probability distribution of the movement of a mobile in all these models typically varies with time and converges to a steady state" distribution (viz. station-ary distribution), whenever the last exists. Protocol per-formance during this transient phase and in steady-state may differ significantly. This justifies the interest in per-fect sampling of the initial node mobility state, so that the simulation of the node mobility is perfect, i.e. it is in steady state throughout a simulation. In this work, we describe im-plementation of the perfect sampling for some random trip models. Our tool produces a perfect sample of the node mobility state, which is then used as input to the widely-used ns-2 network simulator. We further show some simu-lation results for a particular random trip mobility model, based on a real-world road map. The performance met-rics that we consider include various node communication properties and their evolution with time. The results demon-strate difference between transient and steady-state phases and that the transient phase can be long lasting (in the or-der of a typical simulation duration), if the initial state is drawn from a non steady-state distribution. The results give strong arguments in favor to running perfect simula-tions. Our perfect sampling tool is available to public at: http://www.cs.rice.edu/santa/research/mobility.