Generating realistic optical topologies for techno-economic studies using MoleNetwork
Model networks and their underlying topologies have been used as a reference for techno-economic studies for several decades. Existing reference topologies for optical networks may cover different network segments such as backbone, metro core, metro aggregation, access, and/or data center. While telecommunication operators work on the optimization of their own existing deployed optical networks, the availability of different topologies is useful for researchers and technology developers to test their solutions in a variety of scenarios and validate the performance in terms of energy efficiency or cost reduction. This paper presents an open-source tool, MoleNetwork, to generate graphs (backbone, metro core, and metro aggregation) inspired by real network topologies of telecommunication operators that can be used as benchmarks for techno-economic studies. A new topology, to our knowledge, Italy2k, is generated based on the structure of a real operator’s network. Then, the tool is tested by validating that the expected operator parameters are matched in the generated topology and by using the topology to forecast technical demands in a 10-year period in one of its metro regions (core and aggregation networks).
Authors
- Marco Quagliotti (ORCID: https://orcid.org/0000-0003-3571-6319)
- Farhad Arpanaei (ORCID: https://orcid.org/0000-0003-1061-0614)
- Nataliia Koneva
- José Manuel Rivas-Moscoso
- Alfonso Sánchez‐Macián (ORCID: https://orcid.org/0000-0002-2220-0594)
- Juan Pedro Fernández-Palacios Giménez (ORCID: https://orcid.org/0009-0006-1672-6449)
- José Alberto Hernández Gutiérrez (ORCID: https://orcid.org/0000-0002-9551-4308)
Institutions
- Telecom Italia (Italy) (IT)
- Telefonica Research and Development (ES)
- Universidad Carlos III de Madrid (ES)
Publication Details
- Journal
- Journal of Optical Communications and Networking
- Published
- 2025-07-24
- DOI
- https://doi.org/10.1364/jocn.567964
- Primary Topic
- Data Visualization and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00