Markov Modulated Process to Model Human Mobility

Conference paper (2022)

Authors

Brian Chang Student
Liufei Yang Student
M. Sensi Network Architectures and Services - EEMCS
M.A. Achterberg Network Architectures and Services - EEMCS
F. Wang Network Architectures and Services - EEMCS
M. Rinaldi Transport and Planning - CEG
P.F.A. Van Mieghem Network Architectures and Services - EEMCS
Research Group
Network Architectures and Services (EEMCS) (TU Delft)
Copyright: © 2022 Brian Chang, Liufei Yang, M. Sensi, M.A. Achterberg, F. Wang, M. Rinaldi, P.F.A. Van Mieghem
DOI
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https://doi.org/10.1007/978-3-030-93409-5_50
Modeling Markov chains Human mobility Markov modulated process Time-varying networks
More Info
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Published Date

2022

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Quantum & Computer Engineering

Research Group

Network Architectures and Services

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.