This paper investigates offline virtual topology design in transparent optical networks under a multihour traffic demand. The main problem variant addressed here designs a reconfigurable virtual topology that evolves over time to more efficiently utilize network resources (the MH-VTD-R problem). The case of designing a static non-reconfigurable virtual topology that can accommodate the time-varying traffic (the MH-VTD-NR problem) is also considered. The objectives are to minimize: 1) the number of transceivers, which make up for the main network cost; and 2) the frequency of reconfiguration (for MH-VTD-R), which incurs additional overhead and potential service disruption. We formulate this multiobjective problem as an exact mixed integer linear program (MILP). Due to its high complexity, we propose a very efficient heuristic algorithm called Greedy Approach with Reconfiguration Flattening (GARF). GARF not only solves both (non-)reconfigurable problem variants, but it allows for tuning of the relative importance of the two objectives. Exhaustive experiments on real and synthetic traffic and comparison to previous proposals and bounds reveal the merits of GARF with respect to both solution quality and execution time. Furthermore, the obtained results indicate that the maximal transceiver cost savings achieved by the fully reconfigurable case may not be enough to justify the associated increase in reconfiguration cost. However, results show that an advantageous tradeoff between transceiver cost savings and reconfiguration cost can be achieved by a allowing a small number of virtual topology reconfigurations over time.

This paper investigates offline planning and scheduling in transparent optical networks for a given periodic traffic demand. The main objective is to minimize the number of transceivers needed which make up for the main network cost. We call this problem “Scheduled Virtual Topology Design” and consi