TY - JOUR
T1 - Modelling multi-layer spatially embedded random networks
AU - Hackl, Jürgen
AU - Adey, Bryan T.
AU - De Domenico, Manilo
N1 - Funding Information:
The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (grant agreement no. 603960) and the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 636285).
Publisher Copyright:
© 2018 The authors. Published by Oxford University Press. All rights reserved.
PY - 2019/4/1
Y1 - 2019/4/1
N2 - Most real and engineered systems, including transportation infrastructure, are embedded in space and interact with one another in a variety of ways. To study such systems, a novel multi-layer spatially embedded random network model is proposed. In the development of this model, concepts from spatial statistics and graph theory are used to map complex systems with interdependent subsystems to a simplified and condensed mathematical representation. The developed model combines Markov marked point processes for vertex creation, which accounts for spatial distribution, layer assignment, and clustering effects of the vertices, and a hybrid connection model for the edge creation. To test the capabilities of, and gain insights with respect to, a real-world network, the model was used to model a complex infrastructure system, comprised of the power grid and road network of Switzerland. It was found that, even with very simple assumptions, topological properties could be estimated reasonably well.
AB - Most real and engineered systems, including transportation infrastructure, are embedded in space and interact with one another in a variety of ways. To study such systems, a novel multi-layer spatially embedded random network model is proposed. In the development of this model, concepts from spatial statistics and graph theory are used to map complex systems with interdependent subsystems to a simplified and condensed mathematical representation. The developed model combines Markov marked point processes for vertex creation, which accounts for spatial distribution, layer assignment, and clustering effects of the vertices, and a hybrid connection model for the edge creation. To test the capabilities of, and gain insights with respect to, a real-world network, the model was used to model a complex infrastructure system, comprised of the power grid and road network of Switzerland. It was found that, even with very simple assumptions, topological properties could be estimated reasonably well.
KW - multi-layer
KW - random networks
KW - spatially embedded
UR - http://www.scopus.com/inward/record.url?scp=85071116394&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85071116394&partnerID=8YFLogxK
U2 - 10.1093/comnet/cny019
DO - 10.1093/comnet/cny019
M3 - Article
AN - SCOPUS:85071116394
SN - 2051-1310
VL - 7
SP - 254
EP - 280
JO - Journal of Complex Networks
JF - Journal of Complex Networks
IS - 2
M1 - cny019
ER -