MoleNetwork: A tool for the generation of synthetic optical network topologies

TL;DR

The paper addresses the lack of realistic, configurable synthetic optical network topologies for techno-economic studies across backbone, metro core, and metro aggregation. It introduces MoleNetwork, a pluggable Python-based open-source tool that generates backbone, metro core, and metro aggregation topologies using operator-derived statistics from the ALLEGRO project, supporting mesh and ring metro cores, horseshoe aggregation, and integrated backbone-to-metro flows. Validation via thousands of iterations shows that the generated degree and distance distributions closely approximate the target statistics, with GUI and Excel-based outputs enhancing usability for researchers. This framework enables researchers and operators to test capacity, latency, and energy/cost implications across diverse topology scenarios, with future work planned to include access segment generation and AI-driven topology strategies.

Abstract

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 telco 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 inspired by real network topologies of telecommunication operators that can be used as benchmarks for techno-economic studies.

Figures (14)

• Figure 1: Typical hierarchical physical topology of a network operator.
• Figure 2: Sample of a large size metro-regional meshed core network.
• Figure 3: Examples of regional metro core ring structures (in green national nodes, in blue regional nodes).
• Figure 4: Examples of regional metro aggregation horseshoes (in blue regional end nodes, in yellow local aggregation nodes).
• Figure 5: Backbone Generation process.