Algorithms for virtual topology reconfiguration under multi-hour traffic using Lagrangian relaxation and Tabu Search approaches

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.