In his opening OFC plenary talk back in 2021, Alibaba Group’s Yiqun Cai notably added in the follow-up Q&A that today’s complex networks are more than computer science—they grow, they are life. This entails that future networks may be better viewed as techno-social systems that resemble biological superorganisms with brain-like cognitive capabilities. Fast-forwarding, there is now growing awareness that we have to completely change our networks from being static to being a living entity that would act as an AI-powered network “brain,” as recently stated by Bruno Zerbib, Chief Technology and Innovation Officer of France’s Orange, at the Mobile World Congress (MWC) 2025. Even though AI was front and center at both MWC and OFC 2025 and has been widely studied in the context of optical networks, there are currently no publications on active inference in optical (and less so mobile) networks available. Active inference is an ideal methodology for developing more advanced AI systems by biomimicking the way living intelligent systems work while overcoming the limitations of today’s AI related to training, learning, and explainability. Active inference is considered the key to true AI: less artificial, more intelligent. It is a biomimetic mathematical framework that is premised on the first principles of statistical physics found in self-organizing/evolving complex adaptive systems, whether natural, artificial, or hybrid cyborganic ones. The goal of this paper is twofold. First, we aim at enabling optical network researchers to conceptualize new research lines for future optical networks with human-AI interaction capabilities by introducing them to the main mathematical concepts of the active inference framework. Second, we demonstrate how to move AI research beyond the human brain toward the 6G world brain by exploring the role of mycorrhizal networks, the largest living organism on planet Earth, in the AI vision and R&D roadmap for the next decade and beyond laid out by Karl Friston, the father of active inference.
{"title":"From artificial intelligence to active inference: the key to true AI and the 6G world brain [Invited]","authors":"Martin Maier","doi":"10.1364/JOCN.566810","DOIUrl":"https://doi.org/10.1364/JOCN.566810","url":null,"abstract":"In his opening OFC plenary talk back in 2021, Alibaba Group’s Yiqun Cai notably added in the follow-up Q&A that today’s complex networks are more than computer science—they grow, they are life. This entails that future networks may be better viewed as techno-social systems that resemble biological superorganisms with brain-like cognitive capabilities. Fast-forwarding, there is now growing awareness that we have to completely change our networks from being static to being a living entity that would act as an AI-powered network “brain,” as recently stated by Bruno Zerbib, Chief Technology and Innovation Officer of France’s Orange, at the Mobile World Congress (MWC) 2025. Even though AI was front and center at both MWC and OFC 2025 and has been widely studied in the context of optical networks, there are currently no publications on active inference in optical (and less so mobile) networks available. Active inference is an ideal methodology for developing more advanced AI systems by biomimicking the way living intelligent systems work while overcoming the limitations of today’s AI related to training, learning, and explainability. Active inference is considered the key to true AI: less artificial, more intelligent. It is a biomimetic mathematical framework that is premised on the first principles of statistical physics found in self-organizing/evolving complex adaptive systems, whether natural, artificial, or hybrid cyborganic ones. The goal of this paper is twofold. First, we aim at enabling optical network researchers to conceptualize new research lines for future optical networks with human-AI interaction capabilities by introducing them to the main mathematical concepts of the active inference framework. Second, we demonstrate how to move AI research beyond the human brain toward the 6G world brain by exploring the role of mycorrhizal networks, the largest living organism on planet Earth, in the AI vision and R&D roadmap for the next decade and beyond laid out by Karl Friston, the father of active inference.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"18 1","pages":"A28-A43"},"PeriodicalIF":4.3,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145510233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Haipeng Zhang;Zhensheng Jia;Luis Alberto Campos;Curtis Knittle
Coherent passive optical networks (PONs) are a promising solution for next-generation optical access networks, offering high capacity, extended reach, and improved spectral efficiency. This paper presents a single-laser bidirectional (BiDi) coherent PON architecture that supports hybrid single-carrier (SC) and digital subcarrier (DSC) transmission, enabling cost-effective coherent PON implementation and adaptive resource allocation within the same network. The system was experimentally evaluated over a 50 km optical distribution network (ODN) using multiple split ratio configurations, reflecting practical PON deployment scenarios, for both 25 GBd SC and 6.25 GBd DSC transmissions, demonstrating negligible back-reflection penalties compared to conventional full-duplex BiDi schemes. An upstream burst digital signal processing (DSP) framework is proposed, featuring a simple modulation format selection method based on burst rising edge detection and synchronization peak index information, supporting flexible-rate burst-mode upstream transmission across multiple optical network units (ONUs). Experimental results validate the system’s performance across various link distances and split ratios, achieving robust transmission with minimal inter-subcarrier interference. The proposed system offers a cost-effective and scalable solution for next-generation high-speed optical access networks.
{"title":"Single-laser bidirectional coherent PON with hybrid SC and DSC transmission for flexible and cost-effective optical access networks","authors":"Haipeng Zhang;Zhensheng Jia;Luis Alberto Campos;Curtis Knittle","doi":"10.1364/JOCN.571757","DOIUrl":"https://doi.org/10.1364/JOCN.571757","url":null,"abstract":"Coherent passive optical networks (PONs) are a promising solution for next-generation optical access networks, offering high capacity, extended reach, and improved spectral efficiency. This paper presents a single-laser bidirectional (BiDi) coherent PON architecture that supports hybrid single-carrier (SC) and digital subcarrier (DSC) transmission, enabling cost-effective coherent PON implementation and adaptive resource allocation within the same network. The system was experimentally evaluated over a 50 km optical distribution network (ODN) using multiple split ratio configurations, reflecting practical PON deployment scenarios, for both 25 GBd SC and 6.25 GBd DSC transmissions, demonstrating negligible back-reflection penalties compared to conventional full-duplex BiDi schemes. An upstream burst digital signal processing (DSP) framework is proposed, featuring a simple modulation format selection method based on burst rising edge detection and synchronization peak index information, supporting flexible-rate burst-mode upstream transmission across multiple optical network units (ONUs). Experimental results validate the system’s performance across various link distances and split ratios, achieving robust transmission with minimal inter-subcarrier interference. The proposed system offers a cost-effective and scalable solution for next-generation high-speed optical access networks.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"18 1","pages":"A19-A27"},"PeriodicalIF":4.3,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145456030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matheus Sena;Mael Flament;Shane Andrewski;Ioannis Caltzidis;Niccolo Bigagli;Thomas Rieser;Gabriel Bello Portmann;Rourke Sekelsky;Ralf-Peter Braun;Alexander N. Craddock;Maximilian Schulz;Klaus D. Jons;Michaela Ritter;Marc Geitz;Oliver Holschke;Mehdi Namazi
The Quantum Internet, a network of quantum-enabled infrastructure, represents the next frontier in telecommunications, promising capabilities that cannot be attained by classical counterparts. A crucial step in realizing such large-scale quantum networks is the integration of entanglement distribution within existing telecommunication infrastructure. Here, we demonstrate a real-world scalable quantum networking testbed deployed within Deutsche Telekom’s metropolitan fibers in Berlin. Using commercially available quantum devices and standard add-drop multiplexing hardware, we distributed polarization-entangled photon pairs over dynamically selectable looped fiber paths ranging from 10 m to 60 km and showed entanglement distribution over up to approximately 100 km. Quantum signals, transmitted at 1324 nm (O-band), coexist with conventional bidirectional C-band traffic without dedicated fibers or infrastructure changes. Active stabilization of the polarization enables robust long-term performance, achieving entanglement Bell-state fidelity bounds between 85% and 99% and Clauser–Horne–Shimony–Holt parameter $S$-values between 2.36 and 2.74 during continuous multiday operation. By achieving a high-fidelity entanglement distribution with less than 1.5% downtime, we confirm the feasibility of hybrid quantum-classical networks under real-world conditions at the metropolitan scale. These results establish deployment benchmarks and provide a practical roadmap for telecom operators to integrate quantum capabilities.
{"title":"High-fidelity quantum entanglement distribution in metropolitan fiber networks with co-propagating classical traffic","authors":"Matheus Sena;Mael Flament;Shane Andrewski;Ioannis Caltzidis;Niccolo Bigagli;Thomas Rieser;Gabriel Bello Portmann;Rourke Sekelsky;Ralf-Peter Braun;Alexander N. Craddock;Maximilian Schulz;Klaus D. Jons;Michaela Ritter;Marc Geitz;Oliver Holschke;Mehdi Namazi","doi":"10.1364/JOCN.575396","DOIUrl":"https://doi.org/10.1364/JOCN.575396","url":null,"abstract":"The Quantum Internet, a network of quantum-enabled infrastructure, represents the next frontier in telecommunications, promising capabilities that cannot be attained by classical counterparts. A crucial step in realizing such large-scale quantum networks is the integration of entanglement distribution within existing telecommunication infrastructure. Here, we demonstrate a real-world scalable quantum networking testbed deployed within Deutsche Telekom’s metropolitan fibers in Berlin. Using commercially available quantum devices and standard add-drop multiplexing hardware, we distributed polarization-entangled photon pairs over dynamically selectable looped fiber paths ranging from 10 m to 60 km and showed entanglement distribution over up to approximately 100 km. Quantum signals, transmitted at 1324 nm (O-band), coexist with conventional bidirectional C-band traffic without dedicated fibers or infrastructure changes. Active stabilization of the polarization enables robust long-term performance, achieving entanglement Bell-state fidelity bounds between 85% and 99% and Clauser–Horne–Shimony–Holt parameter <tex>$S$</tex>-values between 2.36 and 2.74 during continuous multiday operation. By achieving a high-fidelity entanglement distribution with less than 1.5% downtime, we confirm the feasibility of hybrid quantum-classical networks under real-world conditions at the metropolitan scale. These results establish deployment benchmarks and provide a practical roadmap for telecom operators to integrate quantum capabilities.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 12","pages":"1072-1081"},"PeriodicalIF":4.3,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145456049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Farhad Arpanaei;Mohammadreza Dibaj;Amirhossein Dibaj;Hamzeh Beyranvand;John S. Vardakas;Christos Verikoukis;Jose Manuel Rivas-Moscoso;Juan Pedro Fernandez-Palacios;Alfonso Sanchez-Macian;David Larrabeiti;Jose Alberto Hernandez
As optical networks evolve toward dynamic, multi-band (C $+$ L) architectures, efficient and QoT-aware resource management becomes essential to ensure scalable and low-service downtime operation. This paper introduces a novel, to our knowledge, unified hybrid grooming framework that addresses the unique challenges of traffic grooming in dynamic multi-band elastic optical networks (MB-EONs). Motivated by the need for cost-effective and adaptive high-capacity infrastructures, we propose a policy-based framework incorporating three heuristic algorithms tailored to distinct optimization goals. The unique challenges of multi-band optical networks, such as the non-uniform QoT performance caused by inter-channel stimulated Raman scattering (ISRS) are explicitly considered in our design, as they directly impact grooming efficiency, spectrum utilization, and achievable modulation formats. The algorithms include (i) Min–Max Channel, which minimizes spectrum fragmentation and reduces the partial bit rate blocking probability by up to 35%; (ii) Max Grooming Capacity, which improves line card interface (LCI) reuse and reduces deployment by 20%; and (iii) Time Aware, which minimizes reconfiguration counts by up to 80%, significantly lowering control overhead and service downtime. Unlike prior works limited to static or single-band scenarios, our framework is the first, to our knowledge, to dynamically integrate routing, band selection, modulation format, grooming, and spectrum assignment (RBMGSA) in a QoT-aware manner. Simulation results over the NSFNET, Japan, and Spain topologies under dynamic traffic conditions demonstrate that our approach supports flexible trade-offs among performance, cost, and reconfiguration complexity. Notably, the reconfigurable variants of our algorithms consistently outperform non-reconfigurable approaches by enhancing resource utilization and reducing blocking. The proposed system also supports partial grooming, enabling improved service accommodation and laying the groundwork for scalable and efficient operation in future multi-band optical networks.
{"title":"Evaluating QoT-aware hybrid grooming schemes in dynamic C + L-band optical networks","authors":"Farhad Arpanaei;Mohammadreza Dibaj;Amirhossein Dibaj;Hamzeh Beyranvand;John S. Vardakas;Christos Verikoukis;Jose Manuel Rivas-Moscoso;Juan Pedro Fernandez-Palacios;Alfonso Sanchez-Macian;David Larrabeiti;Jose Alberto Hernandez","doi":"10.1364/JOCN.571277","DOIUrl":"https://doi.org/10.1364/JOCN.571277","url":null,"abstract":"As optical networks evolve toward dynamic, multi-band (C <tex>$+$</tex> L) architectures, efficient and QoT-aware resource management becomes essential to ensure scalable and low-service downtime operation. This paper introduces a novel, to our knowledge, unified hybrid grooming framework that addresses the unique challenges of traffic grooming in dynamic multi-band elastic optical networks (MB-EONs). Motivated by the need for cost-effective and adaptive high-capacity infrastructures, we propose a policy-based framework incorporating three heuristic algorithms tailored to distinct optimization goals. The unique challenges of multi-band optical networks, such as the non-uniform QoT performance caused by inter-channel stimulated Raman scattering (ISRS) are explicitly considered in our design, as they directly impact grooming efficiency, spectrum utilization, and achievable modulation formats. The algorithms include (i) Min–Max Channel, which minimizes spectrum fragmentation and reduces the partial bit rate blocking probability by up to 35%; (ii) Max Grooming Capacity, which improves line card interface (LCI) reuse and reduces deployment by 20%; and (iii) Time Aware, which minimizes reconfiguration counts by up to 80%, significantly lowering control overhead and service downtime. Unlike prior works limited to static or single-band scenarios, our framework is the first, to our knowledge, to dynamically integrate routing, band selection, modulation format, grooming, and spectrum assignment (RBMGSA) in a QoT-aware manner. Simulation results over the NSFNET, Japan, and Spain topologies under dynamic traffic conditions demonstrate that our approach supports flexible trade-offs among performance, cost, and reconfiguration complexity. Notably, the reconfigurable variants of our algorithms consistently outperform non-reconfigurable approaches by enhancing resource utilization and reducing blocking. The proposed system also supports partial grooming, enabling improved service accommodation and laying the groundwork for scalable and efficient operation in future multi-band optical networks.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 12","pages":"1059-1071"},"PeriodicalIF":4.3,"publicationDate":"2025-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145456050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the increasing demand for low-latency deep neural network (DNN) inference, edge-cloud collaborative inference has become a promising paradigm. However, the increasing diversity of models, coupled with the limited and heterogeneous resources of edge nodes, makes it impractical to pre-deploy all models at the edge. These constraints not only intensify the complexity of model partitioning and slice delivery but also impose stricter requirements on scheduling and resource coordination. To address these challenges, this paper proposes a joint optimization approach for model partitioning and slice delivery to improve inference performance. We first formulate a mixed-integer nonlinear programming (MINLP) model for exact optimization. A heuristically seeded genetic algorithm (HSGA) is further developed, which incorporates heuristic initialization and task-driven alternating evolution to improve solution quality and convergence speed. Simulation results demonstrate that the proposed algorithm significantly reduces both the task completion time and blocking rate, validating its effectiveness in complex edge-cloud environments.
{"title":"Joint optimization of DNN model partitioning and slice delivery for distributed edge-cloud inference over optical networks","authors":"Tingting Bao;Xin Li;Yongli Zhao;Meng Lian;Yike Jiang;Jie Zhang","doi":"10.1364/JOCN.575114","DOIUrl":"https://doi.org/10.1364/JOCN.575114","url":null,"abstract":"With the increasing demand for low-latency deep neural network (DNN) inference, edge-cloud collaborative inference has become a promising paradigm. However, the increasing diversity of models, coupled with the limited and heterogeneous resources of edge nodes, makes it impractical to pre-deploy all models at the edge. These constraints not only intensify the complexity of model partitioning and slice delivery but also impose stricter requirements on scheduling and resource coordination. To address these challenges, this paper proposes a joint optimization approach for model partitioning and slice delivery to improve inference performance. We first formulate a mixed-integer nonlinear programming (MINLP) model for exact optimization. A heuristically seeded genetic algorithm (HSGA) is further developed, which incorporates heuristic initialization and task-driven alternating evolution to improve solution quality and convergence speed. Simulation results demonstrate that the proposed algorithm significantly reduces both the task completion time and blocking rate, validating its effectiveness in complex edge-cloud environments.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 11","pages":"1047-1058"},"PeriodicalIF":4.3,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145456029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Roberto Sabella;Luca Valcarenghi;Jun Shan Wey;Yuki Yoshida
This special issue contains 13 papers, of which 5 are invited, relating to hot topics in the area of optical networks, systems, and technologies for future radio access. These topics are gaining increasing importance in mobile network evolutions and related radio systems and could represent relevant elements of innovation in this evolution.
{"title":"Introduction to the special issue on Optical Networks, Systems, and Technologies for Future Radio Access","authors":"Roberto Sabella;Luca Valcarenghi;Jun Shan Wey;Yuki Yoshida","doi":"10.1364/JOCN.582529","DOIUrl":"https://doi.org/10.1364/JOCN.582529","url":null,"abstract":"This special issue contains 13 papers, of which 5 are invited, relating to hot topics in the area of optical networks, systems, and technologies for future radio access. These topics are gaining increasing importance in mobile network evolutions and related radio systems and could represent relevant elements of innovation in this evolution.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 11","pages":"ONST1-ONST2"},"PeriodicalIF":4.3,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11223152","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the Beyond 5G era, networks must deliver not only higher speed and larger capacity but also high reliability and support for massive simultaneous connections. To meet these requirements, we have proposed a smart mobile fronthaul (SMFH) architecture that actively utilizes high-frequency bands and combines analog radio-over-fiber (A-RoF) optical transmission with optically powered remote antennas. Unlike conventional point-to-point A-RoF links, SMFH is distinguished by enabling A-RoF-based mobile fronthaul networking through the insertion of networking functional devices—such as optical switches and optical couplers—into the A-RoF transmission section. In this paper, we construct an A-RoF-based SMFH networking testbed that integrates an open-source software 5G base-station system with an A-RoF transmission module, an optical switch, and an optical coupler in order to verify the networking capabilities of SMFH. Furthermore, we report successful experiments on the testbed that demonstrate key networking capabilities—dynamic serving-cell switching and simultaneous connectivity to multiple cells.
{"title":"Analog radio-over-fiber-based 5G smart mobile fronthaul networking testbed with an open-source software base-station system","authors":"Kojiro Nishimura;Ryuta Murakami;Yoshihiko Uematsu;Satoru Okamoto;Naoaki Yamanaka","doi":"10.1364/JOCN.566706","DOIUrl":"https://doi.org/10.1364/JOCN.566706","url":null,"abstract":"In the Beyond 5G era, networks must deliver not only higher speed and larger capacity but also high reliability and support for massive simultaneous connections. To meet these requirements, we have proposed a smart mobile fronthaul (SMFH) architecture that actively utilizes high-frequency bands and combines analog radio-over-fiber (A-RoF) optical transmission with optically powered remote antennas. Unlike conventional point-to-point A-RoF links, SMFH is distinguished by enabling A-RoF-based mobile fronthaul networking through the insertion of networking functional devices—such as optical switches and optical couplers—into the A-RoF transmission section. In this paper, we construct an A-RoF-based SMFH networking testbed that integrates an open-source software 5G base-station system with an A-RoF transmission module, an optical switch, and an optical coupler in order to verify the networking capabilities of SMFH. Furthermore, we report successful experiments on the testbed that demonstrate key networking capabilities—dynamic serving-cell switching and simultaneous connectivity to multiple cells.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 11","pages":"E144-E154"},"PeriodicalIF":4.3,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11220984","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vignesh Karunakaran;Ronald Romero Reyes;Behnam Shariati;Johannes Karl Fischer;Achim Autenrieth;Thomas Bauschert
With the dynamic nature of optical service provisioning and network topology reconfigurations, failure identification and management become complex, as the machine learning (ML) model is trained for a specific topology with pre-defined performance metrics. This paper proposes a hybrid ML framework for continuous monitoring and soft failure (SF) localization in a partially disaggregated optical network. The framework combines a distributed unsupervised machine learning approach for per-device monitoring and an inductive graph neural network (GNN) for SF localization. This allows the system to generalize across dynamic network conditions, including optical service reconfigurations and node additions or deletions. To support real-time data collection and provide data plane visibility in the management plane, this work proposes gNMI/gRPC-based telemetry streaming using a unified ONF-TAPI YANG data model, enabling vendor-neutral communication across multi-domain networks. The proposed telemetry streaming outperforms the existing solution by reducing traffic load by a factor of 78.4%, and the inductive GNN-based failure localization maintains an accuracy of 97.4% despite dynamic network reconfigurations.
{"title":"Dynamic network-aware soft failure localization using machine learning in optical networks","authors":"Vignesh Karunakaran;Ronald Romero Reyes;Behnam Shariati;Johannes Karl Fischer;Achim Autenrieth;Thomas Bauschert","doi":"10.1364/JOCN.564177","DOIUrl":"https://doi.org/10.1364/JOCN.564177","url":null,"abstract":"With the dynamic nature of optical service provisioning and network topology reconfigurations, failure identification and management become complex, as the machine learning (ML) model is trained for a specific topology with pre-defined performance metrics. This paper proposes a hybrid ML framework for continuous monitoring and soft failure (SF) localization in a partially disaggregated optical network. The framework combines a distributed unsupervised machine learning approach for per-device monitoring and an inductive graph neural network (GNN) for SF localization. This allows the system to generalize across dynamic network conditions, including optical service reconfigurations and node additions or deletions. To support real-time data collection and provide data plane visibility in the management plane, this work proposes gNMI/gRPC-based telemetry streaming using a unified ONF-TAPI YANG data model, enabling vendor-neutral communication across multi-domain networks. The proposed telemetry streaming outperforms the existing solution by reducing traffic load by a factor of 78.4%, and the inductive GNN-based failure localization maintains an accuracy of 97.4% despite dynamic network reconfigurations.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 11","pages":"1032-1046"},"PeriodicalIF":4.3,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Angela Mitrovska;Behnam Shariati;Aydin Jafari;Pooyan Safari;Johannes Karl Fischer;Ronald Freund
The telecommunications industry is undergoing a paradigm shift toward open, disaggregated, and automated networks, necessitating a secure, regulated, and sovereign approach to telemetry data sharing among stakeholders. This paper introduces a pioneering governance framework that leverages the Eclipse Dataspace Components Connector to enforce policy-driven telemetry data exchange within the multi-stakeholder telco ecosystem. The proposed framework offers advanced anonymization mechanisms and dynamic policy-enforcement controls, including stakeholder-specific, time-based, and location-aware access restrictions, ensuring compliance with privacy regulations. In this regard, we propose two novel, to our knowledge, data model vocabularies for modeling the telemetry data sharing problem according to the principles of the International Data Spaces Association, enabling seamless integration and valid application of data sovereignty principles. We experimentally validate the proposed framework through four use-cases designed based on real-world scenarios from operational settings, which address various stakeholder-specific data exchange scenarios, over the Fraunhofer HHI’s software-defined-networking-enabled photonics testbed. We present the policy enforcement capabilities of the framework through various experiments. Additionally, we report an in-depth performance analysis to reveal the latency and communication overhead of the proposed framework compared to conventional telemetry sharing solutions that do not comply with data sovereignty principles. The work in this paper demonstrates innovative contributions that enable data governance within optical networks, driving forward compliance, innovation, and stakeholder collaboration.
电信行业正在经历向开放、分解和自动化网络的范式转变，需要一种安全、规范和独立的方法来实现利益相关者之间的遥测数据共享。本文介绍了一个开创性的治理框架，它利用Eclipse data space Components Connector在多涉众电信生态系统中强制执行策略驱动的遥测数据交换。提议的框架提供高级匿名化机制和动态策略执行控制，包括特定于涉众的、基于时间的和位置感知的访问限制，确保遵守隐私法规。在这方面，我们根据国际数据空间协会的原则提出了两个新颖的数据模型词汇表，用于对遥测数据共享问题进行建模，从而实现数据主权原则的无缝集成和有效应用。我们在弗劳恩霍夫HHI的软件定义网络光子学测试平台上，通过基于操作设置的实际场景设计的四个用例来实验验证所提出的框架，这些用例解决了各种特定于利益相关者的数据交换场景。我们通过各种实验展示了该框架的策略执行能力。此外，我们还报告了一项深入的性能分析，以揭示与不符合数据主权原则的传统遥测共享解决方案相比，所提议框架的延迟和通信开销。本文中的工作展示了实现光网络内数据治理的创新贡献，推动了合规性、创新和利益相关者协作。
{"title":"Network data sharing: a governance framework for ensuring data sovereignty and privacy compliance","authors":"Angela Mitrovska;Behnam Shariati;Aydin Jafari;Pooyan Safari;Johannes Karl Fischer;Ronald Freund","doi":"10.1364/JOCN.559523","DOIUrl":"https://doi.org/10.1364/JOCN.559523","url":null,"abstract":"The telecommunications industry is undergoing a paradigm shift toward open, disaggregated, and automated networks, necessitating a secure, regulated, and sovereign approach to telemetry data sharing among stakeholders. This paper introduces a pioneering governance framework that leverages the Eclipse Dataspace Components Connector to enforce policy-driven telemetry data exchange within the multi-stakeholder telco ecosystem. The proposed framework offers advanced anonymization mechanisms and dynamic policy-enforcement controls, including stakeholder-specific, time-based, and location-aware access restrictions, ensuring compliance with privacy regulations. In this regard, we propose two novel, to our knowledge, data model vocabularies for modeling the telemetry data sharing problem according to the principles of the International Data Spaces Association, enabling seamless integration and valid application of data sovereignty principles. We experimentally validate the proposed framework through four use-cases designed based on real-world scenarios from operational settings, which address various stakeholder-specific data exchange scenarios, over the Fraunhofer HHI’s software-defined-networking-enabled photonics testbed. We present the policy enforcement capabilities of the framework through various experiments. Additionally, we report an in-depth performance analysis to reveal the latency and communication overhead of the proposed framework compared to conventional telemetry sharing solutions that do not comply with data sovereignty principles. The work in this paper demonstrates innovative contributions that enable data governance within optical networks, driving forward compliance, innovation, and stakeholder collaboration.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 11","pages":"1019-1031"},"PeriodicalIF":4.3,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145352176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As emerging technologies advance, the demand for real-time processing of large-scale data grows increasingly critical. This paper focuses on a scenario of serverless edge computing (SEC) supported by optical networks, which integrates SEC’s key features (e.g., auto-scaling and edge deployment of computing resources) with the transmission advantages of optical networks to enable efficient data processing. However, this scenario brings new challenges beyond the scope of traditional task scheduling strategies. On the one hand, task scheduling needs to consider the resource limitations of computing nodes and dependencies between serverless functions; on the other hand, cold start issues caused by the “scale-to-zero” characteristic of SEC significantly impact latency-sensitive tasks. Moreover, existing container warming strategies for mitigating cold start suffer from resource waste and are disconnected from network scheduling. Therefore, this paper proposes a container warming and task scheduling strategy based on reinforcement learning (CWS-RL), which aims to mitigate the impact of cold start, reduce task latency, and control container warming costs. It makes dynamic container warming decisions based on long short-term memory (LSTM) network prediction results and incorporates the dependency slack characteristics of serverless tasks. Meanwhile, it adopts the Deep Deterministic Policy Gradient (DDPG) algorithm to achieve collaborative optimization of container warming and communication scheduling. Compared to the four baseline algorithms, CWS-RL achieves an average latency reduction of 24.08% and an average container warming costs reduction of 17.48%.
{"title":"Task scheduling strategy for mitigating cold start impact in serverless edge computing optical networks","authors":"Shan Yin;Shuyao Wang;Chenyu You;Rongxuan Guo;Mengru Cai;Shanguo Huang","doi":"10.1364/JOCN.561045","DOIUrl":"https://doi.org/10.1364/JOCN.561045","url":null,"abstract":"As emerging technologies advance, the demand for real-time processing of large-scale data grows increasingly critical. This paper focuses on a scenario of serverless edge computing (SEC) supported by optical networks, which integrates SEC’s key features (e.g., auto-scaling and edge deployment of computing resources) with the transmission advantages of optical networks to enable efficient data processing. However, this scenario brings new challenges beyond the scope of traditional task scheduling strategies. On the one hand, task scheduling needs to consider the resource limitations of computing nodes and dependencies between serverless functions; on the other hand, cold start issues caused by the “scale-to-zero” characteristic of SEC significantly impact latency-sensitive tasks. Moreover, existing container warming strategies for mitigating cold start suffer from resource waste and are disconnected from network scheduling. Therefore, this paper proposes a container warming and task scheduling strategy based on reinforcement learning (CWS-RL), which aims to mitigate the impact of cold start, reduce task latency, and control container warming costs. It makes dynamic container warming decisions based on long short-term memory (LSTM) network prediction results and incorporates the dependency slack characteristics of serverless tasks. Meanwhile, it adopts the Deep Deterministic Policy Gradient (DDPG) algorithm to achieve collaborative optimization of container warming and communication scheduling. Compared to the four baseline algorithms, CWS-RL achieves an average latency reduction of 24.08% and an average container warming costs reduction of 17.48%.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 12","pages":"D192-D208"},"PeriodicalIF":4.3,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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