Evolving graphs: Dynamical models, inverse problems and propagation

  • Grindrod P
  • Higham D
  • 74

    Readers

    Mendeley users who have this article in their library.
  • 46

    Citations

    Citations of this article.

Abstract

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. © 2009 The Royal Society

Author-supplied keywords

  • Birth and death process
  • Epidemiology
  • Network
  • Neuroscience
  • Random graph
  • Reproduction rate

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Authors

  • Peter Grindrod

  • Desmond J. Higham

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free