Title
System Identification for Temporal Networks
Author
Shvydun, S. (TU Delft Network Architectures and Services) 
Van Mieghem, P.F.A. (TU Delft Network Architectures and Services)
Date
2023
Abstract
Modelling temporal networks is an open problem that has attracted researchers from a diverse range of fields. Currently, the existing modelling solutions of time-evolving graphs do not allow us to provide an accurate graph sequence. In this paper, we examine the network dynamics from a system identification perspective. We prove that any periodic graph sequence can be accurately modelled as a linear process. We propose two algorithms, called Subspace Graph Generator (SG-gen) and Linear Periodic Graph Generator (LPG-gen), for modelling periodic graph sequences and provide their performance on artificial graph sequences. We further propose a novel model, called Linear Graph Generator (LG-gen), that can be applied to non-periodic graph sequences. Our experiments on artificial and real networks demonstrate that many temporal networks can be accurately approximated by periodic graph sequences.
To reference this document use:
http://resolver.tudelft.nl/uuid:274eea60-4f68-4532-8f5a-9ed00be1ee2a
DOI
https://doi.org/10.1109/TNSE.2023.3333007
Embargo date
2024-05-20
ISSN
2327-4697
Source
IEEE Transactions on Network Science and Engineering, 11 (2), 1885-1895
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.
Part of collection
Institutional Repository
Document type
journal article
Rights
© 2023 S. Shvydun, P.F.A. Van Mieghem