<p>Real-world complex systems exhibit intricate interconnections and dependencies, especially social networks, technological infrastructures, and communication networks. These networks are prone to disconnection due to random failures or external attacks on their components. Therefore, managing the resilience of such networks is a prime concern, particularly at the time of disaster. Therefore, in this research work, the network is reconstructed by rewiring/addition of the edges, and the robustness of the networks is measured. To this aim, two approaches namely (i) Strategic rewiring and (ii) budget-constrained optimal rewiring are adopted. While current research often assesses robustness by examining the size of the largest connected component, this approach fails to capture the complete spectrum of vulnerability. The failure of a small number of connections leads to a sparser yet connected network. Thus, the present research work delves deeper into evaluating the robustness of the restored network by evaluating Laplacian Energy to better comprehend the system’s behavior during the restoration of the network, still considering the size of the largest connected component attacks.</p>

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Novel rewiring mechanism for restoration of the fragmented social networks after attacks

  • Rajesh Kumar,
  • Suchi Kumari,
  • Anubhav Mishra

摘要

Real-world complex systems exhibit intricate interconnections and dependencies, especially social networks, technological infrastructures, and communication networks. These networks are prone to disconnection due to random failures or external attacks on their components. Therefore, managing the resilience of such networks is a prime concern, particularly at the time of disaster. Therefore, in this research work, the network is reconstructed by rewiring/addition of the edges, and the robustness of the networks is measured. To this aim, two approaches namely (i) Strategic rewiring and (ii) budget-constrained optimal rewiring are adopted. While current research often assesses robustness by examining the size of the largest connected component, this approach fails to capture the complete spectrum of vulnerability. The failure of a small number of connections leads to a sparser yet connected network. Thus, the present research work delves deeper into evaluating the robustness of the restored network by evaluating Laplacian Energy to better comprehend the system’s behavior during the restoration of the network, still considering the size of the largest connected component attacks.