Resilience and recovery in complex networks

Abstract

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.