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Critical Phenomena and Optimization in Complex Networks

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".

Deadline for manuscript submissions: closed (28 February 2021)

Special Issue Editor


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Guest Editor
Department of Physics & I3N, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
Interests: complex networks; social (and other) collective phenomena; critical phenomena; spreading processes; interdependent systems.

Special Issue Information

Dear Colleagues,

Biological, social or human-made complex systems exhibit emergent collective phenomena, often arising from the structure and heterogeneity of the interactions between individual elements. Another notable phenomenon observed in complex systems is self-organized criticality.

Complex networks offer an efficient and powerful representation of these interactions. A variety of novel critical phenomena have been observed in complex networks, through exploration of generalized percolation and related processes occurring in networks, directed networks, weighted networks, multilayer networks, and networks of networks. The proximity of the system to a critical state may indicate optimization of information processing or another function. This optimization may be self-organized, or imposed externally. Optimization may be in the form of the process occurring in the network, or in the structure of the network itself.

This Special Issue aims to collect advances in the area of critical phenomena on complex networks, and their relation to and implications for optimization. Contributions may be theoretical or numerical studies of critical phenomena, exploration of or methods for optimization of networks or the processes occurring in them, and studies of self-organized systems.

Dr. Gareth Baxter
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • complex networks
  • critical phenomena
  • self-organized criticality
  • complex systems
  • network optimization
  • processes on networks
  • percolation

Published Papers (2 papers)

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Research

15 pages, 2024 KiB  
Article
More Tolerant Reconstructed Networks Using Self-Healing against Attacks in Saving Resource
by Yukio Hayashi, Atsushi Tanaka and Jun Matsukubo
Entropy 2021, 23(1), 102; https://0-doi-org.brum.beds.ac.uk/10.3390/e23010102 - 12 Jan 2021
Cited by 2 | Viewed by 1952 | Correction
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Critical Phenomena and Optimization in Complex Networks)
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12 pages, 1666 KiB  
Article
Synchronization Dynamics in Non-Normal Networks: The Trade-Off for Optimality
by Riccardo Muolo, Timoteo Carletti, James P. Gleeson and Malbor Asllani
Entropy 2021, 23(1), 36; https://0-doi-org.brum.beds.ac.uk/10.3390/e23010036 - 29 Dec 2020
Cited by 15 | Viewed by 2919
Abstract
Synchronization is an important behavior that characterizes many natural and human made systems that are composed by several interacting units. It can be found in a broad spectrum of applications, ranging from neuroscience to power-grids, to mention a few. Such systems synchronize because [...] Read more.
Synchronization is an important behavior that characterizes many natural and human made systems that are composed by several interacting units. It can be found in a broad spectrum of applications, ranging from neuroscience to power-grids, to mention a few. Such systems synchronize because of the complex set of coupling they exhibit, with the latter being modeled by complex networks. The dynamical behavior of the system and the topology of the underlying network are strongly intertwined, raising the question of the optimal architecture that makes synchronization robust. The Master Stability Function (MSF) has been proposed and extensively studied as a generic framework for tackling synchronization problems. Using this method, it has been shown that, for a class of models, synchronization in strongly directed networks is robust to external perturbations. Recent findings indicate that many real-world networks are strongly directed, being potential candidates for optimal synchronization. Moreover, many empirical networks are also strongly non-normal. Inspired by this latter fact in this work, we address the role of the non-normality in the synchronization dynamics by pointing out that standard techniques, such as the MSF, may fail to predict the stability of synchronized states. We demonstrate that, due to a transient growth that is induced by the structure’s non-normality, the system might lose synchronization, contrary to the spectral prediction. These results lead to a trade-off between non-normality and directedness that should be properly considered when designing an optimal network, enhancing the robustness of synchronization. Full article
(This article belongs to the Special Issue Critical Phenomena and Optimization in Complex Networks)
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