Resilience and recovery in complex networks
In this final year project, we investigate the resilience and recovery of simulated evolving complex network of various edge addition and edge swapping mechanism. This is to better understand which mechanism improves a certain metric in the system that implies the network's resilience against a...
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2016
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sg-ntu-dr.10356-658752023-02-28T23:18:20Z Resilience and recovery in complex networks Sy, Gerico Arquiza Cheong Siew Ann School of Physical and Mathematical Sciences DRNTU::Science::Mathematics::Applied mathematics::Complex systems In this final year project, we investigate the resilience and recovery of simulated evolving complex network of various edge addition and edge swapping mechanism. This is to better understand which mechanism improves a certain metric in the system that implies the network's resilience against attacks that diminish that metric for applications in the recovery real life complex networks. It was found that networks that evolve mainly through the random mechanism in edge addition and edge swapping yields a network where the network connectivity of the network recovers the fastest, implying they are resilient when connectivity is of concern. However, networks that evolve through the preferential attachment mechanism in edge addition and edge swapping yields a network that recovers the fastest in terms of network efficiency or health, and thus, are resilient in this respect. Bachelor of Science in Physics 2016-01-08T08:15:44Z 2016-01-08T08:15:44Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/65875 en 59 p. application/pdf |
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DRNTU::Science::Mathematics::Applied mathematics::Complex systems Sy, Gerico Arquiza Resilience and recovery in complex networks |
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In this final year project, we investigate the resilience and recovery of simulated evolving complex network of various edge addition and edge swapping mechanism. This is to better understand which mechanism improves a certain metric in the system that implies the network's resilience against attacks that diminish that metric for applications in the recovery real life complex networks. It was found that networks that evolve mainly through the random mechanism in edge addition and edge swapping yields a network where the network connectivity of the network recovers the fastest, implying they are resilient when connectivity is of concern. However, networks that evolve through the preferential attachment mechanism in edge addition and edge swapping yields a network that recovers the fastest in terms of network efficiency or health, and thus, are resilient in this respect. |
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Cheong Siew Ann |
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Cheong Siew Ann Sy, Gerico Arquiza |
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Final Year Project |
author |
Sy, Gerico Arquiza |
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Sy, Gerico Arquiza |
title |
Resilience and recovery in complex networks |
title_short |
Resilience and recovery in complex networks |
title_full |
Resilience and recovery in complex networks |
title_fullStr |
Resilience and recovery in complex networks |
title_full_unstemmed |
Resilience and recovery in complex networks |
title_sort |
resilience and recovery in complex networks |
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2016 |
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http://hdl.handle.net/10356/65875 |
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1759857653380546560 |