Algorithms for virtual topology reconfiguration under multi-hour traffic using Lagrangian relaxation and Tabu Search approaches
View/ Open
Share
Statistics
View Usage StatisticsMetadata
Show full item recordAuthor
Aparicio Pardo, Ramón; Pavón Mariño, Pablo; Skorin-Kapov , Nina; García Haro, Juan; García Manrubia, María BelénResearch Group
Grupo de Ingeniería Telemática (GIT)Knowledge Area
Ingeniería TelemáticaPublication date
2010-06Publisher
Institute Electrical and Electronics Engineers. (IEEE)Bibliographic Citation
APARICIO PARDO, R., PAVÓN MARIÑO, P., SKORIN KAPOV, N., GARCÍA MANRUBIA, B., GARCÍA HARO, J. Algorithms for virtual topology reconfiguration under multi-hour traffic using Lagrangian relaxation and Tabu Search approaches. En: International Conference on Transparent Optical Networks (12ª: 2010: Munich (Germany)). 12 th International Conference on Transparent Optical Networks (ICTON 2010), Munich (Germany), June 2010. Munich (Germany): Institute Electrical and Electronics Engineers. 2010. 1-4 p. ISBN 978-1-4244-7799-9Peer review
SíKeywords
Diseño virtual de la topologíaPlanificación de la red
Tráfico multihora
Relajación Lagange
Búsqueda tabú
Virtual topology design
Network planning
Multi-hour traffic
Lagrangian relaxation
Tabu search
Abstract
Periodic reconfiguration of the virtual topology in transparent optical networks has been recently investigated as a mechanism to more efficiently adapt the network to predictable periodic traffic variations along the day or week. The scheduling of periodic reconfigurations should consider the trade-off between a lower network cost obtained through better resource allocation, and the undesired traffic disruptions that these reconfigurations may cause. This paper presents and compares two algorithms for planning virtual topology reconfiguration suitable for exploring this trade-off. The first is based on a Lagrangian relaxation of the planning problem, and the second is based on a Tabu Search meta-heuristic. The merits of both algorithms are compared.
Collections
- Artículos [1734]
The following license files are associated with this item:
Social media