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このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/20000
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| タイトル: | More Tolerant Reconstructed Networks Using Self-Healing against Attacks in Saving Resource |
| 著者: | Hayashi, Yukio
Tanaka, Atsushi
Matsukubo, Jun |
| キーワード: | self-healing
network science
resource allocation
enhancing loops
belief propagation
robustness of connectivity
efficiency of paths
resilience |
| 発行日: | 2021-01-12 |
| 出版者: | MDPI |
| 誌名: | Entropy |
| 巻: | 23 |
| 号: | 1 |
| 開始ページ: | 102 |
| DOI: | 10.3390/e23010102 |
| 抄録: | 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. |
| Rights: | Copyright (c) 2021 Author(s). Yukio Hayashi, Atsushi Tanaka, and Jun Matsukubo. This is an Open Access article distributed under the terms of Creative Commons Licence CC-BY [https://creativecommons.org/licenses/by/4.0/]. Original publication is available on MDPI via https://doi.org/10.3390/e23010102. Correction published on October 26, 2022, see Entropy 2022, 24(11), 1530 at https://doi.org/10.3390/e24111530. |
| URI: | http://hdl.handle.net/10119/20000 |
| 資料タイプ: | publisher |
| 出現コレクション: | d10-1. 雑誌掲載論文 (Journal Articles)
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このアイテムのファイル:
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記述 |
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| T-HAYASHI-Y-0913-11.pdf | | 2028Kb | Adobe PDF | 見る/開く |
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