Abstract
This paper proposes a novel joint resource allocation technique for flexible-grid systems by utilizing non-dominant sort genetic algorithm (NSGA-II) in a multi-objective optimization framework. It pioneers the implementation of an evolutionary mechanism to optimize resources as means of mitigation of physical layer impairments. This investigation initially introduces a proposal in which bandwidth reduction, maximization of the minimum signal-to-noise ratio (SNR) margin, and minimization/maximization of the sum of SNR margins are studied under dual-objective Pareto analysis in the link-level scenario. Later, the technique extends existing provisioning strategies for network planning by targeting the reduction of blocking and spectral utilization of optical connections.
Original language | English |
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Article number | 100648 |
Journal | Optical Switching and Networking |
Volume | 43 |
Early online date | 22 Sept 2021 |
DOIs | |
Publication status | Published - Feb 2022 |
Bibliographical note
© 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/Funding: This work has received partial funding from the EU Horizon 2020 program under the Marie Skodowska-Curie grant agreement No. 813144 (REAL-NET) and the Brazilian National Council for Scientific and Technological Development (CNPq), as well as the institutional support from UFPE and UFBA.
Keywords
- Elastic optical networks
- GN-model
- Genetic algorithms
- Network planning
- Physical layer impairment
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Machine Learning Techniques To Mitigate Nonlinear Impairments In Optical Fiber System
Freire de Carvalho Souza, P. J. (Author), Turitsyn, S. (Supervisor) & Prylepskiy, Y. (Supervisor), Dec 2022Student thesis: Doctoral Thesis › Doctor of Philosophy
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