TY - JOUR
T1 - Percolation and connection times in multi-scale dynamic networks
AU - Hirsch, Christian
AU - Jahnel, Benedikt
AU - Cali, Elie
N1 - Funding Information:
The authors like to thank two anonymous referees for their insightful feedback that helped to substantially improve this manuscript. This research was supported by Orange S.A., France grant CRE G09292 , the German Research Foundation under Germany’s Excellence Strategy MATH: The Berlin Mathematics Research Center, Germany , EXC-2046/1 project ID: 390685689, and the Leibniz Association, Germany within the Leibniz Junior Research Group on Probabilistic Methods for Dynamic Communication Networks as part of the Leibniz Competition. CH acknowledges financial support of the CogniGron research center and the Ubbo Emmius Funds (University of Groningen), Netherlands .
Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2022/9
Y1 - 2022/9
N2 - We study the effects of mobility on two crucial characteristics in multi-scale dynamic networks: percolation and connection times. Our analysis provides insights into the question, to what extent long-time averages are well-approximated by the expected values of the corresponding quantities, i.e., the percolation and connection probabilities. In particular, we show that in multi-scale models, strong random effects may persist in the limit. Depending on the precise model choice, these may take the form of a spatial birth–death process or a Brownian motion. Despite the variety of structures that appear in the limit, we show that they can be tackled in a common framework with the potential to be applicable more generally in order to identify limits in dynamic spatial network models going beyond the examples considered in the present work.
AB - We study the effects of mobility on two crucial characteristics in multi-scale dynamic networks: percolation and connection times. Our analysis provides insights into the question, to what extent long-time averages are well-approximated by the expected values of the corresponding quantities, i.e., the percolation and connection probabilities. In particular, we show that in multi-scale models, strong random effects may persist in the limit. Depending on the precise model choice, these may take the form of a spatial birth–death process or a Brownian motion. Despite the variety of structures that appear in the limit, we show that they can be tackled in a common framework with the potential to be applicable more generally in order to identify limits in dynamic spatial network models going beyond the examples considered in the present work.
KW - Bounded-hop percolation
KW - Continuum percolation
KW - Multi-scale model
KW - Scaling limit
KW - Wireless communication network
UR - http://www.scopus.com/inward/record.url?scp=85133285497&partnerID=8YFLogxK
U2 - 10.1016/j.spa.2022.06.008
DO - 10.1016/j.spa.2022.06.008
M3 - Article
AN - SCOPUS:85133285497
SN - 0304-4149
VL - 151
SP - 490
EP - 518
JO - Stochastic processes and their applications
JF - Stochastic processes and their applications
ER -