Formulation and analysis of mobility points based the semi-Markov model

Based on the random direction mobility model, a Markov mobility network model is designed in this paper. The algorithms and modeling are studied and explained. Poisson distribution is combined with rectangular distribution. The model is realized based on random dynamic simulations. We deduce a set of state transfer functions for the Markov mobility network model in 2D space with a mathematic method. And then, prediction tracking functions are derived. The space-time network is defined as a 3D space including moving objects and their trajectories. The corresponding self-mapping operator is deduced from the state transfer function in 3D space-time network. All of these are validated by simulation experiments.