AI-Native Optical Networks: Machine Learning and AI for Next-Generation Automation, Resilience, and Sustainability
A special issue of Photonics (ISSN 2304-6732). This special issue belongs to the section "Data-Science Based Techniques in Photonics".
Deadline for manuscript submissions: 31 August 2026 | Viewed by 9
Special Issue Editor
Special Issue Information
Dear Colleagues,
As optical networks continue to grow in scale, complexity, and criticality, traditional reactive architectures—reliant on manual intervention and centralized control—are increasingly inadequate for delivering the resilience, agility, and sustainability required by next-generation digital infrastructure. To address these rising demands, this Special Issue seeks to inspire a paradigm shift towards AI-native optical networks, where intelligence is seamlessly embedded throughout the entire network fabric.
In these next-generation systems, artificial intelligence—particularly neuromorphic and photonic AI, as well as large language models (LLMs), alongside advanced machine learning and edge intelligence—serve as foundational enablers. These technologies transform optical infrastructure from merely automated to truly proactive, empowering real-time adaptation, self-healing, zero-touch operation, and sustainable performance.
We invite submissions that advance this vision: from core technologies—including photonic neural networks, spiking neural networks, and distributed multi-agent frameworks—to holistic architectures that enable predictive maintenance, autonomous fault management, resilient and sustainable operation, and intelligent fiber sensing. Contributions addressing real-world integration, deployment challenges, human–AI collaboration, and security are especially encouraged.
Potential topics include, but are not limited to:
- AI-native architectures and self-healing mechanisms for optical networks
- Machine learning and artificial intelligence for resilience, sustainability, and predictive maintenance
- Photonic neural networks, neuromorphic computing, and spiking neural networks for intelligent optical processing
- Large language models (LLMs) and natural language-driven automation in optical networks
- Distributed multi-agent systems for autonomous fault management and network adaptation
- Applications of intelligent fiber sensing and integrated photonic sensing
- Zero-touch provisioning, orchestration, and autonomous network control
- Explainable AI, intent-based networking, and human-in-the-loop collaboration
- Standardization, policy, interoperability, and security in AI-native optical infrastructures
- AI-driven green networking, energy-efficient operation, and sustainable resource management
This Special Issue welcomes original research, visionary perspectives, and comprehensive reviews that chart the course from reactive, human-driven operations to a future of proactive, AI-native optical networks—networks that are adaptive, sustainable, resilient, and ready to meet the demands of next-generation optical networks.
We look forward to receiving your contributions.
Dr. Khouloud Abdelli
Guest Editor
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- AI-native optical networks
- artificial intelligence
- machine learning
- photonic neural networks
- neuromorphic computing
- large language models
- edge intelligence
- self-healing networks
- proactive fault management
- sustainability
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