Recovery of complex networks after intentional attack
Complex networks are often studied upon on their capability to recover and to withstand failure and targeted attack. The complexity of how each component are randomly reconnected can influence the reliability of the complex system. Studies have been done on the error and attack tolerance of complex...
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sg-ntu-dr.10356-783312023-07-07T17:33:58Z Recovery of complex networks after intentional attack Bath, Shaunpal Xiao Gaoxi School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Complex networks are often studied upon on their capability to recover and to withstand failure and targeted attack. The complexity of how each component are randomly reconnected can influence the reliability of the complex system. Studies have been done on the error and attack tolerance of complex systems. However, the recovery strategies were not delved into, to recover the complex system. In this report, several recovery strategies were tested and measured. Comparisons were made amongst the recovery strategies using network performance indicators such as the largest connected component size, and the transition of network density through each recovery strategy process. The findings are as follows: (1) The evaluation of the network recovery performance that is determined by the network performance indicators. (2) The recovery strategies observed had varying outcomes for both efficiencies and limitations. From the results of the simulation of targeted attack and then applying the recovery strategies, it can be concluded that all the recovery strategies were successful. However, in terms of the closeness to the similarity of initial network topology, the random preferential recovery would be the most suitable recovery strategy to recover a scale-free network. Bachelor of Engineering (Information Engineering and Media) 2019-06-18T06:49:49Z 2019-06-18T06:49:49Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/78331 en Nanyang Technological University 49 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Bath, Shaunpal Recovery of complex networks after intentional attack |
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Complex networks are often studied upon on their capability to recover and to withstand failure and targeted attack. The complexity of how each component are randomly reconnected can influence the reliability of the complex system. Studies have been done on the error and attack tolerance of complex systems. However, the recovery strategies were not delved into, to recover the complex system. In this report, several recovery strategies were tested and measured. Comparisons were made amongst the recovery strategies using network performance indicators such as the largest connected component size, and the transition of network density through each recovery strategy process. The findings are as follows: (1) The evaluation of the network recovery performance that is determined by the network performance indicators. (2) The recovery strategies observed had varying outcomes for both efficiencies and limitations. From the results of the simulation of targeted attack and then applying the recovery strategies, it can be concluded that all the recovery strategies were successful. However, in terms of the closeness to the similarity of initial network topology, the random preferential recovery would be the most suitable recovery strategy to recover a scale-free network. |
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Xiao Gaoxi |
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Xiao Gaoxi Bath, Shaunpal |
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Final Year Project |
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Bath, Shaunpal |
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Bath, Shaunpal |
title |
Recovery of complex networks after intentional attack |
title_short |
Recovery of complex networks after intentional attack |
title_full |
Recovery of complex networks after intentional attack |
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Recovery of complex networks after intentional attack |
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Recovery of complex networks after intentional attack |
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recovery of complex networks after intentional attack |
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2019 |
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http://hdl.handle.net/10356/78331 |
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1772826852719591424 |