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

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.

Distributed Self-Healing for Resilient Network Design in Local Resource Allocation Control

“…On the other hand, based on enhancing loops, a new selfhealing method for network reconstruction has been proposed recently [20]. In order to get stronger connectivity, this method applies an extended connection range for new links as the key idea, which has been introduced for interdependent two-layered square lattices [21].…”

“…In order to get stronger connectivity, this method applies an extended connection range for new links as the key idea, which has been introduced for interdependent two-layered square lattices [21]. It has been shown [20] that the reconstructed network has higher robustness than the ones using conventional heuristic methods: simple local repair [22], in which healing links are added by priority of more damaged nodes, and bypass rewiring [23], in which a damaged node is randomly connected only one time with the other one. By Forgiving Tree algorithm [24] in computer science, although the connections between a removed node and its nearest neighbors are replaced as a tree to reduce the diameter of the reconstructed network, this algorithm does not consider the robustness of connectivity.…”

“…By Forgiving Tree algorithm [24] in computer science, although the connections between a removed node and its nearest neighbors are replaced as a tree to reduce the diameter of the reconstructed network, this algorithm does not consider the robustness of connectivity. Despite the advantages [20], it may be expected that the healing method based on enhancing loops is further improved by focusing on the network by the rewirings which has stronger robustness due to smaller gaps between the maximum and minimum degrees [19]. For reducing the gap in the healing after attacks, adding links for low-degree nodes is effective because high-degree nodes tend to be removed.…”

“…Our article is organized as follows: in Section 2, we introduce the outline of our self-healing method in contrast to the previous method [20]. In Section 3, the effects of our method are numerically evaluated by measuring connectivity, robustness of connectivity, and efficiency of paths for typical three real networks.…”

Correction: Hayashi et al. More Tolerant Reconstructed Networks Using Self-Healing against Attacks in Saving Resource. Entropy 2021, 23, 102

“…The authors wish to make the following correction to this paper [ 1 ]. There was a careless mistake in Figure 5 (calculated by using link-based data instead of the usual node-based data for this k avg ( q ) alone): the virtual scale was doubled.…”