Effect of resource constraints on intersimilar coupled networks.
Most real-world networks do not live in isolation but are often coupled together within a larger system. Recent studies have shown that intersimilarity between coupled networks increases the connectivity of the overall system. However, unlike connected nodes in a single network, coupled nodes often share resources, like time, energy, and memory, which can impede flow processes through contention when intersimilarly coupled. We study a model of a constrained susceptible-infected-recovered (SIR) process on a system consisting of two random networks sharing the same set of nodes, where nodes are limited to interact with (and therefore infect) a maximum number of neighbors at each epidemic time step. We obtain that, in agreement with previous studies, when no limit exists (regular SIR model), positively correlated (intersimilar) coupling results in a lower epidemic threshold than negatively correlated (interdissimilar) coupling. However, in the case of the constrained SIR model, the obtained epidemic threshold is lower with negatively correlated coupling. The latter finding differentiates our work from previous studies and provides another step towards revealing the qualitative differences between single and coupled networks.
School of Computer Science, University of St. Andrews, Jack Cole Building, North Haugh, St. Andrews, Fife KY16 9SX, Scotland, UK. saray@cs.st-andrews.ac.uk
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D000465:Algorithms; D001519:Behavior; D001703:Biophysics / Q000379:methods*; D003141:Communicable Diseases / Q000453:epidemiology*; D058872:Epidemics; D006295:Health Resources; D006801:Humans; D012944:Social Support; D013598:Systems Theory