QoT-aware multi-constraint routing in large-scale optical networks based on contraction hierarchies and propagation chains

Multi-constraint routing is a crucial problem in optical networks, as establishing a lightpath must account for multiple constraints, including bandwidth demand, transmission delay, and quality of transmission (QoT). However, the problem-solving complexity increases exponentially due to the addition of constraints such as wavelength contiguity and optical nonlinearity as the network scale increases. Therefore, it is difficult to find a path that satisfies all optical constraints within 10 ms in large-scale topologies. To address these challenges, this paper proposes a QoT-aware multi-constraint routing (QaMcR) algorithm for large-scale optical networks. The algorithm utilizes a contraction hierarchy structure to simplify the topology and employs an enhanced Dijkstra strategy during the routing process, which comprehensively considers transmission delay, bandwidth requirements, and GSNR. Additionally, QaMcR dynamically updates bandwidth usage within the network with low overhead through the time-efficient propagation chain. We simulate both classical and 274-node topologies, using GNPy for physical layer modeling and QoT estimation. A total of 5×10 8 simulations were conducted, exploring nearly a billion shortest paths. The results show that the QaMcR algorithm can find the path with the shortest delay that satisfies multi-constraints within 2 ms, reducing routing time by 95%, while ensuring low delay and low blocking rate.

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Publication Details

Journal
Journal of Optical Communications and Networking
Published
2025-08-11
DOI
https://doi.org/10.1364/jocn.568033
Primary Topic
Advanced Optical Network Technologies
Type
article
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article

QoT-aware multi-constraint routing in large-scale optical networks based on contraction hierarchies and propagation chains

Yongli Zhao, Jiaxing Guo, Pan Yan, Jie Zhang et al.
Journal of Optical Communications and Networking
Advanced Optical Network Technologies
article

QoT-aware multi-constraint routing in large-scale optical networks based on contraction hierarchies and propagation chains

Yongli Zhao, Jiaxing Guo, Pan Yan, Jie Zhang, Yingbo Fan, Yajie Li
article en

Abstract

Multi-constraint routing is a crucial problem in optical networks, as establishing a lightpath must account for multiple constraints, including bandwidth demand, transmission delay, and quality of transmission (QoT). However, the problem-solving complexity increases exponentially due to the addition of constraints such as wavelength contiguity and optical nonlinearity as the network scale increases. Therefore, it is difficult to find a path that satisfies all optical constraints within 10 ms in large-scale topologies. To address these challenges, this paper proposes a QoT-aware multi-constraint routing (QaMcR) algorithm for large-scale optical networks. The algorithm utilizes a contraction hierarchy structure to simplify the topology and employs an enhanced Dijkstra strategy during the routing process, which comprehensively considers transmission delay, bandwidth requirements, and GSNR. Additionally, QaMcR dynamically updates bandwidth usage within the network with low overhead through the time-efficient propagation chain. We simulate both classical and 274-node topologies, using GNPy for physical layer modeling and QoT estimation. A total of 5×10 8 simulations were conducted, exploring nearly a billion shortest paths. The results show that the QaMcR algorithm can find the path with the shortest delay that satisfies multi-constraints within 2 ms, reducing routing time by 95%, while ensuring low delay and low blocking rate.

Journal of Optical Communications and NetworkingVol. 17(10)
Beijing University of Posts and Telecommunications (CN), Tibet University (CN)
Openalex Percentile: Top 81%
Advanced Optical Network Technologies
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QoT-aware multi-constraint routing in large-scale optical networks based on contraction hierarchies and propagation chains — Yongli Zhao, Jiaxing Guo, et al. · Journal of Optical Communications and Networking (2025) | TGRS Research Map | TGRS