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Markov Modulated Process to Model Human Mobility

Conference Paper (2022)
Author(s)

Brian Chang (Student TU Delft)

Liufei Yang (Student TU Delft)

Mattia Sensi (TU Delft - Network Architectures and Services)

Massimo A. Achterberg (TU Delft - Network Architectures and Services)

Fenghua Wang (TU Delft - Network Architectures and Services)

Marco Rinaldi (Transport and Planning)

Piet Van Mieghem (TU Delft - Network Architectures and Services)

Research Group
Network Architectures and Services
DOI related publication
https://doi.org/10.1007/978-3-030-93409-5_50
More Info
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Publication Year
2022
Language
English
Research Group
Network Architectures and Services
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Pages (from-to)
607-618
Publisher
Springer
ISBN (print)
978-3-030-93408-8
Event
10th International Conference on Complex Networks and Their Applications, COMPLEX NETWORKS 2021 (2021-11-30 - 2021-12-02), Hybrid at Madrid, Spain
Downloads counter
340
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Institutional Repository
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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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