Topology Bench: Systematic Graph Based Benchmarking for Core Optical Networks
Robin Matzner, Akanksha Ahuja, Rasoul Sadeghi, Michael Doherty,, Alejandra Beghelli, Seb J. Savory, Polina Bayvel

TL;DR
Topology Bench offers a large, unified dataset of real and synthetic optical network topologies, enabling more systematic benchmarking and analysis of core optical networks through graph-theoretical metrics and machine learning clustering.
Contribution
The paper introduces a comprehensive, publicly accessible dataset of real and synthetic optical network topologies, addressing data fragmentation and scale limitations in prior research.
Findings
Synthetic networks expand the diversity of topologies available.
Graph metrics reveal constraints in real network diversity.
Clustering identifies distinctive topology groups for benchmarking.
Abstract
Topology Bench is a comprehensive topology dataset designed to accelerate benchmarking studies in optical networks. The dataset, focusing on core optical networks, comprises publicly accessible and ready-to-use topologies, including (a) 105 georeferenced real-world optical networks and (b) 270,900 validated synthetic topologies. Prior research on real-world core optical networks has been characterised by fragmented open data sources and disparate individual studies. Moreover, previous efforts have notably failed to provide synthetic data at a scale comparable to our present study. Topology Bench addresses this limitation, offering a unified resource and represents a 61.5% increase in spatially-referenced real world optical networks. To benchmark and identify the fundamental nature of optical network topologies through the lens of graph-theoretical analysis, we analyse both real and…
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Taxonomy
TopicsAdvanced Optical Network Technologies · Optical Network Technologies · Advanced Photonic Communication Systems
