Reinforcing the Resilience of Complex Networks
| dc.creator | Costa, Luciano da Fontoura | |
| dc.date | 2004-01-05 | |
| dc.date.accessioned | 2026-07-07T02:55:43Z | |
| dc.date.available | 2026-07-07T02:55:43Z | |
| dc.description | Given a connected network, it can be augmented by applying a growing strategy (e.g. random or scale-free rules) over the previously existing structure. Another approach for augmentation, recently introduced, involves incorporating a direct edge between any two nodes which are found to be connected through at least one self-avoiding path of length L. This work investigates the resilience of random and scale-free models augmented by using the three schemes identified above. Considering random and scale-free networks, their giant cluster are identified and reinforced, then the resilience of the resulting networks with respect to highest degree node attack is quantified through simulations. The results, which indicate that substantial reinforcement of the resilience of complex networks can be achieved by the expansions, also confirm the superior robustness of the random expansion. | |
| dc.description | 5 pages, 3 figures, 1 table | |
| dc.identifier | https://arxiv.org/abs/cond-mat/0401018 | |
| dc.identifier | http://arxiv.org/abs/cond-mat/0401018 | |
| dc.identifier | Phys. Rev. E 69, 066127 (2004) | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/23041 | |
| dc.subject | Statistical Mechanics | |
| dc.subject | Disordered Systems and Neural Networks | |
| dc.subject | Neurons and Cognition | |
| dc.title | Reinforcing the Resilience of Complex Networks | |
| dc.type | text |