Incremental capacity planning in optical transport networks based on periodic performance metrics

Incremental planning is performed periodically to decide how a backbone optical network has to be updated to serve the forecast traffic during the next planning period. Based on reliable traffic prediction, new equipment is installed and its capacity is ready to be used. Nonetheless, due among others to the introduction of new services, exact prediction is not usually available, which leads to install more capacity than that required thus, increasing network expenditures. To reduce expenses, we propose to monitor some performance metrics and launch the incremental capacity planning problem (INCA) to meet the target performance when some performance metric drops under a threshold. A heuristic algorithm is proposed to solve INCA in practical times. We show that INCA produces savings in terms of used cards with respect to periodical planning thus, demonstrating the utility of our proposal.