Please use this identifier to cite or link to this item: doi:10.22028/D291-31061
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Title: Rejection-Based Simulation of Stochastic Spreading Processes on Complex Networks
Author(s): Großmann, Gerrit
Wolf, Verena
Editor(s): Češka, Milan
Paoletti, Nicola
Language: English
Title: Hybrid systems biology : 6th international workshop
Startpage: 63
Endpage: 79
Publisher/Platform: Springer
Year of Publication: 2019
Place of publication: Cham
Title of the Conference: HSB 2019
Place of the conference: Prague, Czech Republic
Publikation type: Conference Paper
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.
DOI of the first publication: 10.1007/978-3-030-28042-0_5
URL of the first publication: https://link.springer.com/chapter/10.1007/978-3-030-28042-0_5
Link to this record: hdl:20.500.11880/29202
http://dx.doi.org/10.22028/D291-31061
ISBN: 978-3-030-28041-3
978-3-030-28042-0
Date of registration: 29-May-2020
Notes: Lecture notes in computer science ; volume 11705
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Professorship: MI - Prof. Dr. Verena Wolf
Collections:UniBib – Die Universitätsbibliographie

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