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Resilience of complex networks to random breakdown
Gerald Paul1, Sameet Sreenivasan, H Eugene Stanley
1Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215, USA. gerryp@bu.edu
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|December 31, 2005
Summary
This study calculates the critical node removal fraction (fc) for scale-free and bimodal networks using Monte Carlo simulations. Our findings challenge existing theoretical predictions for network robustness.
Area of Science:
- Network science
- Computational physics
- Complex systems analysis
Background:
- Understanding network resilience is crucial for infrastructure and biological systems.
- Previous models, like Cohen's equation, predict the fraction of nodes removed before network collapse.
- The validity of these predictions across different network structures needs verification.
Purpose of the Study:
- To calculate the fraction of nodes removed (fc) before global connectivity loss in scale-free and bimodal networks.
- To compare simulation results with Cohen's theoretical equation for fc.
- To identify the limitations and valid domain of Cohen's equation.
Main Methods:
- Utilizing Monte Carlo simulations to model random node removal.
- Analyzing networks with scale-free and bimodal degree distributions.
- Comparing simulation outcomes for fc against established theoretical predictions.
Main Results:
- Calculated fc values for scale-free and bimodal networks.
- Observed discrepancies between simulation results and Cohen's equation predictions.
- Identified specific network characteristics influencing the accuracy of Cohen's equation.
Conclusions:
- Cohen's equation for fc is not universally applicable to all network types.
- Simulation-based calculations provide a more accurate measure of network robustness for certain distributions.
- The study clarifies the conditions under which Cohen's equation remains valid, refining network resilience analysis.
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