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Optical Network Digital Twin -- Commercialization Barriers, Value Proposition, Early Use Cases, and Challenges

Hideki Nishizawa, Toru Mano, Kazuya Anazawa, Tatsuya Matsumura, Takeo Sasai, Masatoshi Namiki, Dmitrii Briantcev, Renato Ambrosone, Esther Le Rouzic, Stefan Melin, Oscar Gonzalez-de-Dios, Juan Pedro Fernandez-Palacios, Xiaocheng Zhang, Keigo Akahoshi, Gert Grammel, Andrea D'Amico, Giacomo Borraccini, Marco Ruffini, Daniel Kilper, Vittorio Curri

TL;DR

This paper addresses the commercialization barriers of optical network digital twins by proposing a GN-model-based ONDT that delivers end-to-end QoT management for light paths in AI-driven networks. It details an architecture where AWGN-based QoT estimation, enabled by tools like GNPy and the GGn model, supports real-time, per-LP provisioning across multi-vendor, multi-domain environments. The authors outline value propositions, depict early use cases (alien wavelengths, DCX, and multi-operator interconnections), and identify challenges such as extending models to additional impairments, standardizing interfaces, and ensuring secure orchestration. The work lays out a practical roadmap for evolving optical networks toward flexible, automated operation suitable for data-center interconnects and large-scale AI workloads, with measurable benefits in provisioning speed, reliability, and efficiency.

Abstract

With the widespread adoption of AI, machine-to-machine communications are rapidly increasing, reshaping the requirements for optical networks. Recent advances in Gaussian noise modeling for digital coherent transmission have raised expectations for digital-twin-based operation. However, unlike digital twins in wireless communication, which are already well established, significant barriers remain for commercialization in optical networks. This paper discusses the evolving requirements of optical networks in the AI era and proposes an Optical Network Digital Twin architecture that enables flexible end-to-end light path operation beyond conventional management. The value propositions of the proposed architecture, its evolutionary steps toward commercialization, and key research challenges for practical deployment are presented.

Optical Network Digital Twin -- Commercialization Barriers, Value Proposition, Early Use Cases, and Challenges

TL;DR

This paper addresses the commercialization barriers of optical network digital twins by proposing a GN-model-based ONDT that delivers end-to-end QoT management for light paths in AI-driven networks. It details an architecture where AWGN-based QoT estimation, enabled by tools like GNPy and the GGn model, supports real-time, per-LP provisioning across multi-vendor, multi-domain environments. The authors outline value propositions, depict early use cases (alien wavelengths, DCX, and multi-operator interconnections), and identify challenges such as extending models to additional impairments, standardizing interfaces, and ensuring secure orchestration. The work lays out a practical roadmap for evolving optical networks toward flexible, automated operation suitable for data-center interconnects and large-scale AI workloads, with measurable benefits in provisioning speed, reliability, and efficiency.

Abstract

With the widespread adoption of AI, machine-to-machine communications are rapidly increasing, reshaping the requirements for optical networks. Recent advances in Gaussian noise modeling for digital coherent transmission have raised expectations for digital-twin-based operation. However, unlike digital twins in wireless communication, which are already well established, significant barriers remain for commercialization in optical networks. This paper discusses the evolving requirements of optical networks in the AI era and proposes an Optical Network Digital Twin architecture that enables flexible end-to-end light path operation beyond conventional management. The value propositions of the proposed architecture, its evolutionary steps toward commercialization, and key research challenges for practical deployment are presented.

Paper Structure

This paper contains 11 sections, 5 figures.

Table of Contents

  1. Introduction
  2. Optical network digital twin architecture
  3. Digital Twin Model
  4. OLS types (Managed/unmanaged)
  5. Value proposition
  6. Early use cases
  7. Alien wavelength via conventional ring
  8. Data center exchange
  9. Multi-operator interconnection
  10. Future challenges
  11. Conclusion

Figures (5)

  • Figure 1: Comparison of ONs and wireless networks
  • Figure 2: Optical network digital twin architecture
  • Figure 3: QoT visualization
  • Figure 4: Changes in OLS types and operational methods
  • Figure 5: Early use cases for optical network digital twins