AI & ML
Optical Network Digital Twin: From Digital Coherent Transmission to Intelligent Network Operations
arXiv cs.SY0 views
arXiv:2611.08217v1 Announce Type: new Abstract: Optical Network Digital Twins (ONDTs) are emerging as a key framework for representing, synchronizing, and utilizing the physical state of optical networks for quality-of-transmission (QoT) estimation, optimization, and intelligent operation. This survey provides a comprehensive view of ONDTs, spanning digital coherent transmission and physical-layer observability to intelligent network operations. We systematically organize ONDT technologies from ecosystem, functional, control, and implementation architecture perspectives and review the enabling technologies required to construct, synchronize, and utilize digital representations of physical optical networks. As a unifying framework to describe both ONDT design and validation, we introduce a categorization based on the following figures of merit: Fidelity, Dynamicity, and Deployability (FDD). In particular, we emphasize fit-for-purpose Fidelity, where modeling effort focuses on the physical effects of components rather than solely maximizing model accuracy, favoring scalability and generalizability. Furthermore, experimental and field validations are examined to evaluate the practical applicability of ONDT technologies. We further examine experimental and field validations, from physics-based QoT estimation and measurement-informed model refinement to field synchronization, service provisioning, multi-domain observability, and infrastructure characterization. Finally, we discuss the complementary roles of ONDTs and AI agents toward autonomous optical networks and identify key research directions for practical deployment.
Source:https://arxiv.org/abs/2611.08217PreviousOvercoming Fundamental Control Limitations in Powered Descent Flight through Robust Incremental Nonlinear Dynamic InversionNextOutput-Feedback Integral Sliding-Mode Extremum Seeking with Super-Twisting Differentiation
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