Heuristic Approaches for Periodic Reconfiguration of Lightpath-based Networks under Multi-hour Traffic

Abstract

Periodic lightpath reconfiguration of virtual topologies in transparent optical networks has been recently investigated as a mechanism to more efficiently adapt the network to predictable periodic traffic variations along a day or week. Scheduling periodic reconfigurations involves tuning a trade-off between a lower network cost obtained through better resource allocation, and undesired traffic disruptions that these reconfigurations may cause. This paper presents and compares two algorithms for planning a reconfigurable virtual topology suitable for exploring this trade-off. The first is based on a Lagrangean Relaxation of the planning problem, and the second is based on a Tabu Search meta-heuristic. The merits of both algorithms are assessed for moderate network sizes through comparison with analytical lower bounds and exact solutions obtained by a MILP formulation.