Network Resilience and Robustness: Theory and Applications

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Original Research
31 January 2022

UAV swarm are often subjected to random interference or malicious attacks during the execution of their tasks, resulting in UAV failure or communication interruption. When the UAV swarm is out of interference or the repair command is executed, the performance of the UAV swarm will be restored to a certain extent. However, how to measure the changes of UAV swarm’s performance during this process will be very important, and it is also crucial to determine whether the UAVs can continue to perform its mission. Based on this motivation, we propose a resilience assessment framework for UAV swarm considering load balancing after UAV swarm suffer from disturbances. We analyze the effects of different topologies and different parameters on the resilience of UAV swarm. The study found that attack intensity is the most important factor affecting UAV swarm performance. As the attack intensity increases, the performance of the UAV swarm decreases rapidly. At the same time, topology also has a very important impact on UAV swarm resilience.

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Schematic illustration of interacting network with different topological structures. (A) Every sub-network is coupled to all other sub-networks from inter-connected coupling pattern in the Ref. [50]. And, different colors denote different topological structures of sub-networks. (B) Each sub-network has connections to other specific sub-networks not all other sub-networks from [26]. Network A follows a power-law degree distribution. Sub-networks a and b within network A follow Poisson sub-degree distribution. The links in network A follow the Poisson inter-degree distribution, as shown in sub-networks c.
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Original Research
20 December 2021
Network Robustness Analysis Based on Maximum Flow
Meng Cai
1 more and 
Ying Cui
(A) Flow recovery robustness of four typical networks under deliberate attack. (B) Flow recovery robustness of four typical networks under random attack.

Network robustness is the ability of a network to maintain a certain level of structural integrity and its original functions after being attacked, and it is the key to whether the damaged network can continue to operate normally. We define two types of robustness evaluation indicators based on network maximum flow: flow capacity robustness, which assesses the ability of the network to resist attack, and flow recovery robustness, which assesses the ability to rebuild the network after an attack on the network. To verify the effectiveness of the robustness indicators proposed in this study, we simulate four typical networks and analyze their robustness, and the results show that a high-density random network is stronger than a low-density network in terms of connectivity and resilience; the growth rate parameter of scale-free network does not have a significant impact on robustness changes in most cases; the greater the average degree of a regular network, the greater the robustness; the robustness of small-world network increases with the increase in the average degree. In addition, there is a critical damage rate (when the node damage rate is less than this critical value, the damaged nodes and edges can almost be completely recovered) when examining flow recovery robustness, and the critical damage rate is around 20%. Flow capacity robustness and flow recovery robustness enrich the network structure indicator system and more comprehensively describe the structural stability of real networks.

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7 citations
Original Research
25 November 2021
A Study on Drivers of Water Consumption in China From a Complex Network Perspective
Ruijin Du
5 more and 
Guochang Fang
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Water consumption has been one of the most important topics in the field of environment and economy. Even though the driving factors of water consumption have been well studied, it is still a daunting task to reveal the influence of the status of provinces in the entire supply chain. By combining the multi-regional input-output (MRIO) model and complex network theory, an inter-provincial virtual water transfer (V WT) network was constructed to analyze the overall structural characteristics of the network model and identify the structural roles of each province. The constructed inter-provincial V WT network exhibited the characteristics of a small-world network, that is, virtual water can be easily transferred from one province to another. Moreover, network analysis revealed that provinces with different positions in the V WT network played discrepant structural roles. Panel regression analysis was further used to quantify the impact of provincial structural roles on their water consumption. The results showed that water consumption in China largely depended on some structural role characteristics in the V WT network. Out-degree and out-strength characterizing the ability of direct exporting virtual water exerted significant positive influences, while in-closeness featuring the indirect virtual water importing rate had a significant negative effect on water usage. This indicated that adjusting the uneven provincial consumption structure, the direct production demand of downstream provinces and the indirect production activities in the supply chain would help reduce water consumption. Therefore, to come true the goal of water conservation in China, it would be necessary to improve the trade structure between direct and indirect exporters and importers in the entire supply chain.

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Frontiers in Physics

Exploring Human Interactions through Sociophysics: Dynamics of Opinion Formation
Edited by Francisco Welington Lima, Alireza Abbasi, Michele Bellingeri, Roy Lindelauf, Valerio Restocchi, Xiu-Xiu Zhan
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