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Temporal Graph Reproduction with RWIG

Journal Article (2025)
Author(s)

S. Shvydun (TU Delft - Network Architectures and Services)

Anton David Almasan (TU Delft - Network Architectures and Services)

PFA van Mieghem (TU Delft - Network Architectures and Services)

Research Group
Network Architectures and Services
DOI related publication
https://doi.org/10.1109/TNSE.2025.3555974
More Info
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Publication Year
2025
Language
English
Research Group
Network Architectures and Services
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. 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. @en
Issue number
4
Volume number
12
Pages (from-to)
3015-3024
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

We examine the Random Walkers Induced temporal Graph (RWIG) model, which generates temporal graphs based on the co-location principle of M independent walkers that traverse the underlying Markov graph with different transition probabilities. Given the assumption that each random walker is in the steady state, we determine the steady-state vector s̃and the Markov transition matrix P
i of each walker w
i that can reproduce the observed temporal network G
0, . . ., G
K
–1 with the lowest mean squared error. We also examine the performance of RWIG for periodic temporal graph sequences.

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