Network Pruning and Growth - Probabilistic Optimization


Being the backbone of many human-made systems, networks require both pruning and growth to adapt to changing demand. We develop a message passing-based framework for analyzing and addressing the two-level optimization problem of edge removal/addition for indirectly-dependent objectives. As exemplar problem we use routing in optical communication networks to minimize capability loss (removal) or maximize capacity (addition). The methods developed result in lower path-lengths and higher capacity topologies with respect to existing ones and are suitable for a broad range of network design tasks.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Applied Mathematics & Data Science
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies
College of Engineering & Physical Sciences > Aston Centre for Artifical Intelligence Research and Application
Additional Information: Acknowledgements: DS and YZX acknowledge support from the EPSRC Programme Grant TRANSNET (EP/R035342/1). Copyright: Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.
Uncontrolled Keywords: complex systems,computational complexity,network flow optimization,network formation and growth,Network Optimisation
Publication ISSN: 2643-1564
Last Modified: 04 Jul 2024 07:26
Date Deposited: 26 Jul 2023 14:57
Full Text Link:
Related URLs: https://journal ... search.5.033087 (Publisher URL)
PURE Output Type: Article
Published Date: 2023-08-08
Published Online Date: 2023-08-08
Accepted Date: 2023-07-22
Authors: Xu, Yi-Zhi
Saad, David (ORCID Profile 0000-0001-9821-2623)



Version: Accepted Version

Access Restriction: Restricted to Repository staff only


Version: Published Version

License: Creative Commons Attribution

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