Complex networks underpin many of the world's critical systems, from the Internet to transportation infrastructures and social structures. While studying these networks has gained traction in disciplines like network theory and graph theory, a pressing concern has emerged around their resilience and robustness. Resilience refers to a network's ability to recover from disruptions and adapt to maintain its functionality. Conversely, robustness gauges a network's inherent strength against failures, ensuring continuity of operations even when parts of the system collapse. These attributes are fundamental in ensuring that the networks upon which society relies can withstand various challenges, from targeted cyber-attacks to unexpected natural disasters. The research topic "Topology and Turbulence: Examining the Resilience and Robustness of Complex Networks" aims to dive deep into these aspects, shedding light on designing resilient and robust networks.
Despite the considerable progress in understanding complex networks, there needs to be more knowledge regarding the influence of different network topologies on the robustness and resilience of these systems. Many real-world networks are susceptible to disruptions, from targeted attacks and random failures to spreading diseases or misinformation. A comprehensive study can be conducted to understand how network structures respond to these disruptions, identifying which topologies offer more resilience against different perturbations. This research could entail the development of computational models to simulate these disruptions and evaluate the subsequent network response. The findings of this Research Topic could inform the design of more resilient networks in various domains, like robust social media platforms resistant to misinformation spread, dependable infrastructure systems, and more effective strategies for disease control in epidemiological networks.
This Research Topic aims to delve into the resilience and robustness of complex networks against various disruptions. We encourage submissions that explore but are not limited to, the following themes: 1) Influence of Network Topologies on Resilience: Examining how different network structures affect the system's resilience—comparative analysis of scale-free, small-world, random, and other network topologies under varying conditions; 2) Disruptions in Networks: Studies addressing the effects of targeted attacks, random failures, or the spread of diseases or misinformation on complex networks; 3) Simulation Models: Development and utilization of computational models to simulate disruptions and analyze the subsequent network response; 4) Case Studies: Real-world applications and case studies, for example, in social networks, infrastructure systems, epidemiological networks, or computer networks; 5) Strategies for Resilience: Proposals for strategies to increase network resilience based on network structure and dynamics, including designing networks to be more robust or creating strategies to respond to network disruptions.
Keywords:
Network Theory, Graph Theory, Social Networks, Scale-free Networks, Network Dynamics, Small-world Networks, Resilient Network Systems, Robust networks
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Complex networks underpin many of the world's critical systems, from the Internet to transportation infrastructures and social structures. While studying these networks has gained traction in disciplines like network theory and graph theory, a pressing concern has emerged around their resilience and robustness. Resilience refers to a network's ability to recover from disruptions and adapt to maintain its functionality. Conversely, robustness gauges a network's inherent strength against failures, ensuring continuity of operations even when parts of the system collapse. These attributes are fundamental in ensuring that the networks upon which society relies can withstand various challenges, from targeted cyber-attacks to unexpected natural disasters. The research topic "Topology and Turbulence: Examining the Resilience and Robustness of Complex Networks" aims to dive deep into these aspects, shedding light on designing resilient and robust networks.
Despite the considerable progress in understanding complex networks, there needs to be more knowledge regarding the influence of different network topologies on the robustness and resilience of these systems. Many real-world networks are susceptible to disruptions, from targeted attacks and random failures to spreading diseases or misinformation. A comprehensive study can be conducted to understand how network structures respond to these disruptions, identifying which topologies offer more resilience against different perturbations. This research could entail the development of computational models to simulate these disruptions and evaluate the subsequent network response. The findings of this Research Topic could inform the design of more resilient networks in various domains, like robust social media platforms resistant to misinformation spread, dependable infrastructure systems, and more effective strategies for disease control in epidemiological networks.
This Research Topic aims to delve into the resilience and robustness of complex networks against various disruptions. We encourage submissions that explore but are not limited to, the following themes: 1) Influence of Network Topologies on Resilience: Examining how different network structures affect the system's resilience—comparative analysis of scale-free, small-world, random, and other network topologies under varying conditions; 2) Disruptions in Networks: Studies addressing the effects of targeted attacks, random failures, or the spread of diseases or misinformation on complex networks; 3) Simulation Models: Development and utilization of computational models to simulate disruptions and analyze the subsequent network response; 4) Case Studies: Real-world applications and case studies, for example, in social networks, infrastructure systems, epidemiological networks, or computer networks; 5) Strategies for Resilience: Proposals for strategies to increase network resilience based on network structure and dynamics, including designing networks to be more robust or creating strategies to respond to network disruptions.
Keywords:
Network Theory, Graph Theory, Social Networks, Scale-free Networks, Network Dynamics, Small-world Networks, Resilient Network Systems, Robust networks
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.