Implementation of QoT-Aware Hybrid Grooming Schemes in Dynamic C+L-Band Optical Networks: Source Codes and Datasets

This repository contains the complete Python implementation and datasets used in the paper.It includes simulations for three optical network topologies — NSFNET, JPAN, and Spain —evaluated under reconfigurable and non-reconfigurable case.Each case has been tested using three algorithms:• Min–Max Channel• Max Grooming• Time-AwareAll results and figures used in the paper are generated directly from these scripts.The folder organization and naming follow the structure below.2. Folder StructureMain DirectoriesFolder Description0_Final_resultsa-Data Contains all generated results and final figures in .eps format.1_JPAN_Data_main_code JPAN network simulation data and main Python code.2_spain_Data_main_code Spain network simulation data and main Python code.3_NSFNET_main_code NSFNET network simulation data and main Python code.Subfolder 0_Final_resultsaDataDescriptionfinal_EPS_paper_Figs/ Contains .eps format figures of results used in the paper.JP_network_result/ Excel files containing simulation data of results for JPAN network.SP_network_result/ Excel files containing simulation data of results for Spain network.NSFNET_network_result/ Excel files containing simulation data of results for NSFNETnetwork.Inside Each Network Folder (1_JPAN_Data_main_code, 2_spain_Data_main_code,3_NSFNET_main_code)Subfolder DescriptionData_tables_OSNR/ OSNR-related data tables used for modulation format selection.code/ Main executable Jupyter files and supporting scripts. Includes subfolders foreach algorithm.Each algorithm folder (1_Min_Max_channel, 2_Max_grooming, 3_time_aware) contains:• A Jupyter notebook file (code.ipynb) — the main executable script for that case.• Supporting JSON and Excel input files.3. System and Environment• Processor: Intel(R) Core(TM) i7-8550U CPU @ 1.80 GHz• RAM: 8 GB (7.43 GB usable)• The code was verified to execute correctly in this environment.4. Python Environment• Python version: 3.10.0• Required libraries:To install required libraries in Python, we “requirements.txt” file which contains allthe used modules and their corresponding version. Please run this command to havecompatible version of each module:1. pip install requirements.txtAll Python files use relative paths, ensuring smooth execution on any local machine.5. Notes• Each “code.ipynb” file includes all necessary function definitions and imports at thebeginning — only Python 3.10 and the above libraries are needed.6. CitationIf you use this code or data, please cite the corresponding JOCN article