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Markov Modulated Process to Model Human Mobility

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Complex Networks & Their Applications X (COMPLEX NETWORKS 2021)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1072))

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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.

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Notes

  1. 1.

    This paper is a bridgement of the master theses of B. Chang [4] and L. Yang [25].

  2. 2.

    The Python code of our mobility simulator is available on GitHub: https://github.com/twente/mmp-mobility-model.

  3. 3.

    The spacing in the lattice is \(10/6 \approx 1.667\) which exceeds \(d=1.5\); therefore, there are no links in the initial graph at \(k=0\).

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Acknowledgements

The authors thank Dr. ir. Sascha Hoogendoorn-Lanser for sharing the library data, which has been collected as part of an ongoing project led by her at TU Delft.

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Authors and Affiliations

  1. Delft University of Technology, 2628 CD, Delft, The Netherlands

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

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  1. Brian Chang
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  2. Liufei Yang
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  3. Mattia Sensi
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  4. Massimo A. Achterberg
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  5. Fenghua Wang
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  7. Piet Van Mieghem
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Corresponding author

Correspondence to Mattia Sensi .

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Editors and Affiliations

  1. Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Madrid, Madrid, Spain

    Rosa Maria Benito

  2. IUT Lumière, University of Lyon, Bron Cedex, France

    Chantal Cherifi

  3. LIB, UFR Sciences et Techniques, University of Burgundy, Dijon, France

    Hocine Cherifi

  4. Grupo Interdisciplinar de Sistemas Complejos, Universidad Carlos III de Madrid, Leganés, Madrid, Spain

    Esteban Moro

  5. Thomas J. Watson College of Engineering and Applied Science, Binghamton University, Binghamton, USA

    Luis M. Rocha

  6. Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Tarragona, Spain

    Marta Sales-Pardo

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Chang, B. et al. (2022). Markov Modulated Process to Model Human Mobility. In: Benito, R.M., Cherifi, C., Cherifi, H., Moro, E., Rocha, L.M., Sales-Pardo, M. (eds) Complex Networks & Their Applications X. COMPLEX NETWORKS 2021. Studies in Computational Intelligence, vol 1072. Springer, Cham. https://doi.org/10.1007/978-3-030-93409-5_50

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  • DOI: https://doi.org/10.1007/978-3-030-93409-5_50

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