Graph coloring framework to mitigate cascading failure in complex networks
Abstract Cascading failures pose a significant threat to the stability and functionality of complex systems, making their mitigation a crucial area of research. While existing strategies aim to enhance network robustness, identifying an optimal set of critical nodes that mediates the cascade for pro...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | Communications Physics |
| Online Access: | https://doi.org/10.1038/s42005-025-02089-y |
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| Summary: | Abstract Cascading failures pose a significant threat to the stability and functionality of complex systems, making their mitigation a crucial area of research. While existing strategies aim to enhance network robustness, identifying an optimal set of critical nodes that mediates the cascade for protection remains a challenging task. Here, we present a robust and pragmatic framework that effectively mitigates the cascading failures by strategically identifying and securing critical nodes within the network. Our approach leverages a graph coloring technique to identify the critical nodes using the local network topology, and results in a minimal set of critical nodes to be protected yet maximally effective in mitigating the cascade thereby retaining a large fraction of the network intact. Our method outperforms existing mitigation strategies across diverse network configurations and failure scenarios. An extensive empirical validation using real-world networks highlights the practical utility of our framework, offering a promising tool for enhancing network robustness in complex systems. |
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| ISSN: | 2399-3650 |