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Improving Robustness of Complex Net-works through Centrality Metrics Analysis

Sayahi, Ali | 2015

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 48401 (52)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Ghorshi, Mohammad Ali; Kavousi, Kaveh
  7. Abstract:
  8. Complex Networks are everywhere, many complex systems can be represented as networks, such as the power grid, the road network, the airline network and the Protein-protein interaction network, delivery and distribution networks, and telephone networks. A fundamental issue concerning complex networks is the robustness of the overall system to the failure of its constituent parts. The robustness of networks against failure, targeted attacks to individuals’ components, and the impact on the performance of the system has become an important issue for practical reasons in the last few years. The failures attacks or errors on networks are not limited to the deletion of vertex, for common measure vertex deletion, and the edge deletion. Vertex adding and edge adding can make the network more fragile. By adding vertices or edges on networks may make some important centrality edges over vertices more important. This will increase the risk of attacks on the important vertices or edges. To mitigate the attacks on vertices, researchers have proposed many solutions to improve the robustness of complex networks. These solutions typically involved a reconfiguration of the networks edges. In this Thesis we extend the studies by investigating the effects of removing edges from network structure on the robustness of the network. Different centrality measures and other indicators such as clustering coefficient were analyzed on a variety of empirical networks
  9. Keywords:
  10. Robustness ; Complex Network ; Network Structural Features ; Clustering ; Centrality Metrics

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