Markov Modulated Process to Model Human Mobility

Brian Chang, Liufei Yang, Mattia Sensi, Massimo A. Achterberg, Fenghua Wang, Marco Rinaldi, Piet Van Mieghem

Abstract: We introduce a Markov Modulated Process (MMP) to describe human mobility. We represent the mobility process as a time-varying graph, where a link specifies a connection between two nodes (humans) at any discrete time step. Each state of the Markov chain encodes a certain modification to the original graph. We show that our MMP model successfully captures the main features of a random mobility simulator, in which nodes moves in a square region. We apply our MMP model to human mobility, measured in a library.