Topology Bench: systematic graph-based benchmarking for core optical networks

作者：Robin Matzner, Akanksha Ahuja, Rasoul Sadeghi, Michael Doherty, Alejandra Beghelli, Seb J. Savory, Polina Bayvel · 发表于：Journal of Optical Communications and Networking · 年份：2024 · DOI：10.1364/jocn.534477 · 被引用次数：21 · 研究领域：Advanced Optical Network Technologies、Optical Network Technologies、Advanced Photonic Communication Systems

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 characterized 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 analyze both real and synthetic networks using structural, spatial, and spectral metrics. Our comparative analysis identifies constraints in real optical network diversity and illustrates how synthetic networks can complement and expand the range of topologies available for use. Currently, topologies are selected based on subjective criteria, such as preference, data availability, or perceived suitability, leading to potential biases and limited representativeness. Our framework enhances the generalizability of optical network research by providing a more objective and systematic approach to topology selection. A stati...