English

Distributed flow optimization and cascading effects in weighted complex networks

Physics and Society 2019-12-18 v1 Statistical Mechanics Social and Information Networks

Abstract

We investigate the effect of a specific edge weighting scheme (kikj)β\sim (k_i k_j)^{\beta} on distributed flow efficiency and robustness to cascading failures in scale-free networks. In particular, we analyze a simple, yet fundamental distributed flow model: current flow in random resistor networks. By the tuning of control parameter β\beta and by considering two general cases of relative node processing capabilities as well as the effect of bandwidth, we show the dependence of transport efficiency upon the correlations between the topology and weights. By studying the severity of cascades for different control parameter β\beta, we find that network resilience to cascading overloads and network throughput is optimal for the same value of β\beta over the range of node capacities and available bandwidth.

Keywords

Cite

@article{arxiv.1110.3832,
  title  = {Distributed flow optimization and cascading effects in weighted complex networks},
  author = {Andrea Asztalos and Sameet Sreenivasan and Boleslaw K. Szymanski and G. Korniss},
  journal= {arXiv preprint arXiv:1110.3832},
  year   = {2019}
}
R2 v1 2026-06-21T19:21:44.108Z