Evolving graphs: dynamical models, inverse problems and propagation

Grindrod, P. and Higham, D. J. (2010) Evolving graphs: dynamical models, inverse problems and propagation. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 466 (2115). pp. 753-770. ISSN 1364-5021 doi: 10.1098/rspa.2009.0456

Abstract/Summary

Applications such as neuroscience, telecommunication, online social networking, transport and retail trading give rise to connectivity patterns that change over time. In this work, we address the resulting need for network models and computational algorithms that deal with dynamic links. We introduce a new class of evolving range-dependent random graphs that gives a tractable framework for modelling and simulation. We develop a spectral algorithm for calibrating a set of edge ranges from a sequence of network snapshots and give a proof of principle illustration on some neuroscience data. We also show how the model can be used computationally and analytically to investigate the scenario where an evolutionary process, such as an epidemic, takes place on an evolving network. This allows us to study the cumulative effect of two distinct types of dynamics.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/2052
Identification Number/DOI	10.1098/rspa.2009.0456
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics > Centre for the Mathematics of Human Behaviour (CMOHB)
Publisher	Royal Society Publishing
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