Novel Evolutionary Planning Technique for Flexible-grid Transmission in Optical Networks


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.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > Aston Institute of Photonics Technology (AIPT)
Additional Information: © 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International 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.
Uncontrolled Keywords: Elastic optical networks,GN-model,Genetic algorithms,Network planning,Physical layer impairment,Computer Networks and Communications,Electrical and Electronic Engineering
Publication ISSN: 1573-4277
Last Modified: 12 Jun 2024 07:21
Date Deposited: 27 Sep 2021 08:02
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Related URLs: https://www.sci ... 57342772100045X (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2022-02
Published Online Date: 2021-09-22
Accepted Date: 2021-09-16
Authors: Sena, Matheus R.
Freire, Pedro J. (ORCID Profile 0000-0003-3145-1018)
Coelho, Leonardo D.
Santos, Alex F.
Napoli, Antonio
Almeida, Raul C.

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