More Tolerant Reconstructed Networks Using Self-Healing against Attacks in Saving Resource

Hayashi, Yukio and Tanaka, Atsushi and Matsukubo, Jun (2021) More Tolerant Reconstructed Networks Using Self-Healing against Attacks in Saving Resource. Entropy, 23 (1). p. 102. ISSN 1099-4300

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Abstract

Complex network infrastructure systems for power supply, communication, and transportation support our economic and social activities; however, they are extremely vulnerable to frequently increasing large disasters or attacks. Thus, the reconstruction of a damaged network is more advisable than an empirically performed recovery of the original vulnerable one. To reconstruct a sustainable network, we focus on enhancing loops so that they are not trees, which is made possible by node removal. Although this optimization corresponds with an intractable combinatorial problem, we propose self-healing methods based on enhancing loops when applying an approximate calculation inspired by statistical physics. We show that both higher robustness and efficiency are obtained in our proposed methods by saving the resources of links and ports when compared to ones in conventional healing methods. Moreover, the reconstructed network can become more tolerant than the original when some damaged links are reusable or compensated for as an investment of resource. These results present the potential of network reconstruction using self-healing with adaptive capacity in terms of resilience.

Item Type: Article
Uncontrolled Keywords: Keywords: self-healing; network science; resource allocation; enhancing loops; belief propagation; robustness of connectivity; efficiency of paths; resilience
Subjects: STM Repository > Physics and Astronomy
Depositing User: Managing Editor
Date Deposited: 09 May 2023 05:18
Last Modified: 16 Jul 2024 06:56
URI: http://classical.goforpromo.com/id/eprint/451

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