Node Survival in Networks under Correlated Attacks.
We study the interplay between correlations, dynamics, and networks for repeated attacks on a socio-economic network. As a model system we consider an insurance scheme against disasters that randomly hit nodes, where a node in need receives support from its network neighbors. The model is motivated by gift giving among the Maasai called Osotua. Survival of nodes under different disaster scenarios (uncorrelated, spatially, temporally and spatio-temporally correlated) and for different network architectures are studied with agent-based numerical simulations. We find that the survival rate of a node depends dramatically on the type of correlation of the disasters: Spatially and spatio-temporally correlated disasters increase the survival rate; purely temporally correlated disasters decrease it. The type of correlation also leads to strong inequality among the surviving nodes. We introduce the concept of disaster masking to explain some of the results of our simulations. We also analyze the subsets of the networks that were activated to provide support after fifty years of random disasters. They show qualitative differences for the different disaster scenarios measured by path length, degree, clustering coefficient, and number of cycles.
Department of Mathematics and Computer Science, Hobart and William Smith Colleges, Geneva, New York, United States of America.
Yan
Y
Hao
School of Mathematical and Statistical Sciences, Arizona State University, Tempe, Arizona, United States of America.
Dieter
D
Armbruster
School of Engineering and Science, Jacobs University, Bremen, Germany.
Marc-Thorsten
MT
Hütt
D000818:Animals; D016000:Cluster Analysis; D003198:Computer Simulation; D004190:Disasters; D037921:Gift Giving; D006801:Humans; D008962:Models, Theoretical; D012944:Social Support; D015996:Survival Rate; D013997:Time Factors