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International Workshop on Hybrid Systems Biology

HSB 2019: Hybrid Systems Biology pp 63–79Cite as

Rejection-Based Simulation of Stochastic Spreading Processes on Complex Networks

Part of the Lecture Notes in Computer Science book series (LNBI,volume 11705)

Abstract

Stochastic processes can model many emerging phenomena on networks, like the spread of computer viruses, rumors, or infectious diseases. Understanding the dynamics of such stochastic spreading processes is therefore of fundamental interest. In this work we consider the wide-spread compartment model where each node is in one of several states (or compartments). Nodes change their state randomly after an exponentially distributed waiting time and according to a given set of rules. For networks of realistic size, even the generation of only a single stochastic trajectory of a spreading process is computationally very expensive.

Here, we propose a novel simulation approach, which combines the advantages of event-based simulation and rejection sampling. Our method outperforms state-of-the-art methods in terms of absolute runtime and scales significantly better while being statistically equivalent.

Keywords

  • Spreading process
  • SIR
  • Epidemic modeling
  • Monte-Carlo simulation
  • Gillespie Algorithm

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Notes

  1. 1.

    github.com/gerritgr/Rejection-Based-Epidemic-Simulation.

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Acknowledgments

This research has been partially funded by the German Research Council (DFG) as part of the Collaborative Research Center “Methods and Tools for Understanding and Controlling Privacy”. We thank Michael Backenköhler for his comments on the manuscript.

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Authors and Affiliations

  1. Saarland University, 66123, Saarbrücken, Germany

    Gerrit Großmann & Verena Wolf

Authors
  1. Gerrit Großmann
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  2. Verena Wolf
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Corresponding author

Correspondence to Gerrit Großmann .

Editor information

Editors and Affiliations

  1. Brno University of Technology, Brno, Czech Republic

    Milan Češka

  2. University of London, Royal Holloway, Egham, UK

    Dr. Nicola Paoletti

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Großmann, G., Wolf, V. (2019). Rejection-Based Simulation of Stochastic Spreading Processes on Complex Networks. In: Češka, M., Paoletti, N. (eds) Hybrid Systems Biology. HSB 2019. Lecture Notes in Computer Science(), vol 11705. Springer, Cham. https://doi.org/10.1007/978-3-030-28042-0_5

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  • DOI: https://doi.org/10.1007/978-3-030-28042-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-28041-3

  • Online ISBN: 978-3-030-28042-0

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