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Static resource allocation for dynamic traffic

Xu, Y.; Agrell, E.; Brandt Pearce, M. (September 2019, Proceedings of the 45th European Conference on Optical Communication)

A flexible offline probabilistic (FOP) algorithm is designed to aggressively accommodate random bandwidth traffic demands in long-haul networks. Compared to algorithms that configure demands according to their maximum bandwidth, the FOP algorithm can save 15% of the spectrum used, accommodating over 99% of the throughput demand.
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Probabilistic spectrum Gaussian noise estimate for random bandwidth traffic

Xu, Y.; Agrell, E.; Brandt Pearce, M. (September 2019, Proceedings of the 45th European Conference on Optical Communication)

A probabilistic spectrum Gaussian noise (PSGN) model is proposed to predict the nonlinear noise for random bandwidth traffic in long-haul elastic optical networks. The model reduces the noise estimate 9.1% on average compared to the standard Gaussian noise model applied to the maximum bandwidth.
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Regenerator Allocation in Nonlinear Elastic Optical Networks With Random Data Rates

https://doi.org/10.1364/OFC.2018.Th2A.47

Yan, L.; Xu, Y.; Brandt-Pearce, M.; Dharmaweera, N.; Agrell, E. (January 2018, Optical Fiber Conference)

We optimize the regenerator allocation in nonlinear elastic networks whose traffic demands have random data rates. Compared with previous regenerator allocation algorithm, our method achieves the same blocking probability with 11% less regenerator sites.
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