Abstract

TopoLib is an open-source Python library providing a curated collection of core network topologies and analytical traffic models for rapid network evaluation. The library includes 60 optical core networks sourced from operator websites, scientific literature, and research projects. Each topology contains node geo-locations, population figures, and per-node counts of data centers (DCs) and Internet exchange points (IXPs), along with link interconnections and distances. Three analytical traffic models are provided: two state-of-the-art models [gravitational and multi-period traffic (MPT)], and the proposed region aggregation model (RAM), which estimates traffic based on population, DCs, and IXPs. Applied to a topology, these models produce a traffic matrix suitable for network evaluation and cross-study comparison. All data can be exported for external use, and researchers may load their own topologies and modify model parameters to suit their specific needs. To demonstrate the library, three topologies are evaluated across nine distinct cases, covering three analyses: a comparison of traffic generated by each model, a sensitivity analysis of the RAM components, and a case study integrating TopoLib with MONET, a multi-period optical network planning tool based on Flex Net Sim [J. Opt. Commun. Netw.18, D16 (2026)], showcasing how the library can support exhaustive network utilization and infrastructure deployment studies.