Resilient routing and spectrum assignment in Elastic Optical Networks under Dynamic Traffic

Sammanfattning: Transparent Elastic Optical Networks (EON) are seen as a promising solution for future optical transport networks to keep up with internet traffic growth, as they allow provisioning connections with different bandwidth requirements in an efficient way. To achieve high spectrum efficiency in these networks, making good Routing, Modulation and Spectrum Assignment (RMLSA) decisions is essential. Since fiber cuts are common, resiliency against single-link failures is another important topic. This can be provided efficiently through shared-path protection (SPP), which in turn complicates the RMLSA problem. Existing routing, modulation and spectrum assignment algorithms for SPP focus on the two-step approach, where primary paths are selected independently of their backup path options. However, selecting a different primary path can allow for a better backup path with higher shareability of backup resources if primary and backup path pairs are considered together. Previous studies on SPP in EONs mostly consider the static traffic scenario. Under a dynamic traffic scenario, where unpredictable connection re-quests arrive and terminate over time, fragmentation of spectral resources has a significant impact on the network performance. In this thesis, a new algorithm is proposed for SPP in EONs against single-link failures where primary and backup path pairs are selected jointly, thereby minimizing fragmentation and maximizing shareability which leads to better network performance in terms of blocking probability. Unlike existing algorithms, the primary and backup path and spectrum are decided simultaneously from a set of candidate path pairs and the spectrum assignment is done using a hybrid cost metric. The metric is a weighted combination of existing metrics that integrates fragmentation and shareability into a multi-objective function. Using network traffic simulations in two reference networks, the effect of the different cost functions on the algorithm’s behavior is explored and an optimal set of weights is determined. With this parameterization, traffic simulations in a scaled-down sample US network topology with load values of 190-240 Erlang, corresponding to blocking probabilities of 0.1% to 1%, show an average improvement over the reference algorithm of 79% in blocking probability, 6.9% in shareability and 5.9% in spectrum fragmentation. It is also shown that most of this improvement is caused by joint primary-backup path assignments. The hybrid cost function reduces blocking by a further 10%.