| Autor(es): |
de Lima, Leandro Alvarez
;
Pavani, Gustavo Sousa
;
Ahmed, T
;
Festor, O
;
Ghamri-Doudane, Y
;
Kang, JM
;
Schaeffer-Filho, AE
;
Lahmadi, A
;
Madeira, E
Número total de Autores: 9
|
| Tipo de documento: | Artigo Científico |
| Fonte: | 2021 IFIP/IEEE INTERNATIONAL SYMPOSIUM ON INTEGRATED NETWORK MANAGEMENT (IM 2021); v. N/A, p. 5-pg., 2021-01-01. |
| Resumo | |
Artificial intelligence techniques may play a significant role in the control of elastic optical networks by offering improved performance over traditional dynamic provisioning and recovery methods. In this work, we propose a fully distributed routing algorithm based on the Ant Colony Optimization (ACO) meta-heuristics associated with crankback re-routing extensions. Simulations have demonstrated that the proposed ACO-based algorithm outperforms the fixed-alternate approach. They also demonstrate that the proposed approach achieves similar levels of bandwidth blocking probability and restorability compared to an adaptive routing algorithm that relies on the OSPF-TE routing protocol, with much lower levels of control overhead, comparable levels of setup time, and without a significant increase in the restoration time. We also evaluate the trade-offs in using a trunk reservation policy for the proposed approach. (AU) | |
| Processo FAPESP: | 15/24341-7 - Novas estratégias para enfrentar a ameaça de exaustão da capacidade |
| Beneficiário: | Helio Waldman |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |