Nested Dirichlet process for collaborative mobility modeling

Mobility modeling is the mathematical modeling of mobile users´ (cars, cell phone users) movement patterns. The resulting model not only provides us with an understanding of past mobile user movements, but also enables us to predict how a mobile user might move in the future. It has been found useful in both infrastructure-based wireless network and ad hoc network for protocol evaluation, resource planning, etc. A nonparametric hierarchical Bayesian approach is proposed in this paper for extracting hierarchical mobility patterns from mobile user traces. Experiment results show that the proposed method is able to generate a hierarchical mobility model that better reflect the mobility pattern structure in many scenarios. It also has better future movement prediction compared to the hidden Markov model.