Anna Tzanakaki;Markos Anastasopoulos;Victoria-Maria Alevizaki
This study focuses on the development of an intent-based networking (IBN) control and management framework automating operations of beyond 5G (B5G) infrastructures supported by optical transport networks to interconnect radio access and core networks. Currently, these infrastructures operate in accordance with the software defined networking (SDN) and network function virtualization (NFV) paradigm, relying on complex northbound and southbound interfaces to expose their (network) capabilities and apply suitable configuration policies to B5G infrastructure. B5G infrastructures are expected to operate over complex heterogeneous transport network and compute domains, each having its own programming language and interfaces. To address the increased complexity of this approach, the present study relies on generative artificial intelligence (GenAI) and large language models (LLMs) to significantly simplify the interaction between different layers and domains through automated translation of configuration policies from one domain to another. More specifically, the developed GenAI models are used to support automated operations of B5G infrastructures by 1) translating high-level intents provided by network operators expressed in the form of natural language into autogenerated optimization code used by the orchestrator and 2) creating autoconfiguration policies for the optical transport network. The semantic accuracy and complexity of the proposed framework to generate appropriate configuration policies are experimentally tested over an optical transport network interconnecting the radio access and core networks of a B5G infrastructure.
{"title":"Intent-based control and management framework for optical transport networks supporting B5G services empowered by large language models [Invited]","authors":"Anna Tzanakaki;Markos Anastasopoulos;Victoria-Maria Alevizaki","doi":"10.1364/JOCN.534909","DOIUrl":"https://doi.org/10.1364/JOCN.534909","url":null,"abstract":"This study focuses on the development of an intent-based networking (IBN) control and management framework automating operations of beyond 5G (B5G) infrastructures supported by optical transport networks to interconnect radio access and core networks. Currently, these infrastructures operate in accordance with the software defined networking (SDN) and network function virtualization (NFV) paradigm, relying on complex northbound and southbound interfaces to expose their (network) capabilities and apply suitable configuration policies to B5G infrastructure. B5G infrastructures are expected to operate over complex heterogeneous transport network and compute domains, each having its own programming language and interfaces. To address the increased complexity of this approach, the present study relies on generative artificial intelligence (GenAI) and large language models (LLMs) to significantly simplify the interaction between different layers and domains through automated translation of configuration policies from one domain to another. More specifically, the developed GenAI models are used to support automated operations of B5G infrastructures by 1) translating high-level intents provided by network operators expressed in the form of natural language into autogenerated optimization code used by the orchestrator and 2) creating autoconfiguration policies for the optical transport network. The semantic accuracy and complexity of the proposed framework to generate appropriate configuration policies are experimentally tested over an optical transport network interconnecting the radio access and core networks of a B5G infrastructure.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 1","pages":"A112-A123"},"PeriodicalIF":4.0,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825945","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}
Machine learning (ML)-based quality-of-transmission (QoT) estimation tools will be desirable for operating virtual network topologies (VNTs) that disclose only abstracted views of connectivity and resource availability to tenants. Conventional ML-based solutions rely on laborious human effort on model selection, parameter tuning, and so forth, which can cause prolonged model building time. This paper exploits the learning-to-learn nature by meta learning to pursue automated provisioning of QoT estimators for a dynamic VNT configuration in optical networks. In particular, we first propose a graph neural network (GNN) design for network-wide QoT estimation. The proposed design learns global VNT representations by disseminating and merging features of virtual nodes (conveying transmitter-side configurations) and links (characterizing physical line systems) according to the routing schemes used. Consequently, the GNN is able to predict the QoT for all the end-to-end connections in a VNT concurrently. A distributed collaborative learning method is also applied for preserving data confidentiality. We train a meta GNN with meta learning to acquire knowledge generalizable across tasks and realize automated QoT estimator provisioning by fine tuning the meta model with a few new samples for each incoming VNT request. Simulation results using data from two realistic topologies show our proposal can generalize QoT estimation for VNTs of arbitrary structures and improves the estimation accuracy by up to 18.7% when compared with the baseline.
{"title":"Meta-learning-aided QoT estimator provisioning for a dynamic VNT configuration in optical networks","authors":"Xiaoliang Chen;Zhenlin Ouyang;Hanyu Gao;Qunzhi Lin;Zuqing Zhu","doi":"10.1364/JOCN.534417","DOIUrl":"https://doi.org/10.1364/JOCN.534417","url":null,"abstract":"Machine learning (ML)-based quality-of-transmission (QoT) estimation tools will be desirable for operating virtual network topologies (VNTs) that disclose only abstracted views of connectivity and resource availability to tenants. Conventional ML-based solutions rely on laborious human effort on model selection, parameter tuning, and so forth, which can cause prolonged model building time. This paper exploits the learning-to-learn nature by meta learning to pursue automated provisioning of QoT estimators for a dynamic VNT configuration in optical networks. In particular, we first propose a graph neural network (GNN) design for network-wide QoT estimation. The proposed design learns global VNT representations by disseminating and merging features of virtual nodes (conveying transmitter-side configurations) and links (characterizing physical line systems) according to the routing schemes used. Consequently, the GNN is able to predict the QoT for all the end-to-end connections in a VNT concurrently. A distributed collaborative learning method is also applied for preserving data confidentiality. We train a meta GNN with meta learning to acquire knowledge generalizable across tasks and realize automated QoT estimator provisioning by fine tuning the meta model with a few new samples for each incoming VNT request. Simulation results using data from two realistic topologies show our proposal can generalize QoT estimation for VNTs of arbitrary structures and improves the estimation accuracy by up to 18.7% when compared with the baseline.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 1","pages":"A103-A111"},"PeriodicalIF":4.0,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142821267","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}
Fiber-based quantum key distribution (QKD) systems are mature and commercialized, but their integration into existing optical networks is crucial for their widespread use, in particular in passive optical networks (PONs) if end-to-end quantum-secured communications are to be addressed. While discrete-variable QKD coexistence with classical channels is well-studied in point-to-point links, its performance in point-to-multipoint topologies like PONs has received less attention. We thus developed a numerical tool to estimate quantum-available bandwidth and maximum link lengths for QKD systems in single-fiber PON architectures in coexistence with GPON, XG-PON, NG-PON2, and HS-PON standards. The QKD channel performance is obtained by setting thresholds on the quantum bit error rate and the secret key rate, ultimately limited by spontaneous Raman scattering noise and high optical distribution network losses. We perform a comparison between the performance obtained assuming the asymptotic infinite-key generation rate or taking into account actual implementations in the finite-key regime. We evidence that proper design rules can be obtained as a function of both classical and quantum system parameters to support end-to-end quantum security services in existing optical networks.
{"title":"Discrete-variable quantum key distribution services hosted in legacy passive optical networks [Invited]","authors":"Alessandro Gagliano;Alberto Gatto;Pierpaolo Boffi;Paolo Martelli;Paola Parolari","doi":"10.1364/JOCN.534366","DOIUrl":"https://doi.org/10.1364/JOCN.534366","url":null,"abstract":"Fiber-based quantum key distribution (QKD) systems are mature and commercialized, but their integration into existing optical networks is crucial for their widespread use, in particular in passive optical networks (PONs) if end-to-end quantum-secured communications are to be addressed. While discrete-variable QKD coexistence with classical channels is well-studied in point-to-point links, its performance in point-to-multipoint topologies like PONs has received less attention. We thus developed a numerical tool to estimate quantum-available bandwidth and maximum link lengths for QKD systems in single-fiber PON architectures in coexistence with GPON, XG-PON, NG-PON2, and HS-PON standards. The QKD channel performance is obtained by setting thresholds on the quantum bit error rate and the secret key rate, ultimately limited by spontaneous Raman scattering noise and high optical distribution network losses. We perform a comparison between the performance obtained assuming the asymptotic infinite-key generation rate or taking into account actual implementations in the finite-key regime. We evidence that proper design rules can be obtained as a function of both classical and quantum system parameters to support end-to-end quantum security services in existing optical networks.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 1","pages":"A96-A102"},"PeriodicalIF":4.0,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810660","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}
We explore optical switching to extend network programmability to the physical layer and discuss applications of a Layer-1 software-defined network (SDN) in AI/HPC clusters. In this context we identify two applications for optical circuit switches (OCSs): failure resilience and reconfigurable topologies for deep learning workloads. We present experimental results from a DGX-based testbed towards improving failure resilience and a simulation analysis for efficient deep learning training in AI clusters.
{"title":"Optical switching for data centers and advanced computing systems [Invited]","authors":"Giannis Patronas;Nikos Terzenidis;Prethvi Kashinkunti;Eitan Zahavi;Dimitris Syrivelis;Louis Capps;Zsolt-Alon Wertheimer;Nikos Argyris;Athanasios Fevgas;Craig Thompson;Avraham Ganor;Julie Bernauer;Elad Mentovich;Paraskevas Bakopoulos","doi":"10.1364/JOCN.534317","DOIUrl":"https://doi.org/10.1364/JOCN.534317","url":null,"abstract":"We explore optical switching to extend network programmability to the physical layer and discuss applications of a Layer-1 software-defined network (SDN) in AI/HPC clusters. In this context we identify two applications for optical circuit switches (OCSs): failure resilience and reconfigurable topologies for deep learning workloads. We present experimental results from a DGX-based testbed towards improving failure resilience and a simulation analysis for efficient deep learning training in AI clusters.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 1","pages":"A87-A95"},"PeriodicalIF":4.0,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810662","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}
Robin Matzner;Akanksha Ahuja;Rasoul Sadeghi;Michael Doherty;Alejandra Beghelli;Seb J. Savory;Polina Bayvel
Topology Bench is a comprehensive topology dataset designed to accelerate benchmarking studies in optical networks. The dataset, focusing on core optical networks, comprises publicly accessible and ready-to-use topologies, including (a) 105 georeferenced real-world optical networks and (b) 270,900 validated synthetic topologies. Prior research on real-world core optical networks has been characterized by fragmented open data sources and disparate individual studies. Moreover, previous efforts have notably failed to provide synthetic data at a scale comparable to our present study. Topology Bench addresses this limitation, offering a unified resource, and represents a 61.5% increase in spatially referenced real-world optical networks. To benchmark and identify the fundamental nature of optical network topologies through the lens of graph-theoretical analysis, we analyze both real and synthetic networks using structural, spatial, and spectral metrics. Our comparative analysis identifies constraints in real optical network diversity and illustrates how synthetic networks can complement and expand the range of topologies available for use. Currently, topologies are selected based on subjective criteria, such as preference, data availability, or perceived suitability, leading to potential biases and limited representativeness. Our framework enhances the generalizability of optical network research by providing a more objective and systematic approach to topology selection. A statistical and correlation analysis reveals the quantitative range of all of these graph metrics and the relationships between them. Finally, we apply unsupervised machine learning to cluster real-world topologies into distinctive groups based on nine optimal graph metrics using K-means. It employs a two-step optimization process: optimal features are selected by maximizing feature uniqueness through principal component analysis, and the optimal number of clusters is determined by maximizing decision boundary distances via support vector machines. We conclude the analysis by providing guidance on how to use such clusters to select a diverse set of topologies for future studies. Topology Bench, openly available via Dataset 1 (https://zenodo.org/records/13921775) and Code 1 (https://github.com/TopologyBench), promotes accessibility, consistency, and reproducibility.
{"title":"Topology Bench: systematic graph-based benchmarking for core optical networks","authors":"Robin Matzner;Akanksha Ahuja;Rasoul Sadeghi;Michael Doherty;Alejandra Beghelli;Seb J. Savory;Polina Bayvel","doi":"10.1364/JOCN.534477","DOIUrl":"https://doi.org/10.1364/JOCN.534477","url":null,"abstract":"Topology Bench is a comprehensive topology dataset designed to accelerate benchmarking studies in optical networks. The dataset, focusing on core optical networks, comprises publicly accessible and ready-to-use topologies, including (a) 105 georeferenced real-world optical networks and (b) 270,900 validated synthetic topologies. Prior research on real-world core optical networks has been characterized by fragmented open data sources and disparate individual studies. Moreover, previous efforts have notably failed to provide synthetic data at a scale comparable to our present study. Topology Bench addresses this limitation, offering a unified resource, and represents a 61.5% increase in spatially referenced real-world optical networks. To benchmark and identify the fundamental nature of optical network topologies through the lens of graph-theoretical analysis, we analyze both real and synthetic networks using structural, spatial, and spectral metrics. Our comparative analysis identifies constraints in real optical network diversity and illustrates how synthetic networks can complement and expand the range of topologies available for use. Currently, topologies are selected based on subjective criteria, such as preference, data availability, or perceived suitability, leading to potential biases and limited representativeness. Our framework enhances the generalizability of optical network research by providing a more objective and systematic approach to topology selection. A statistical and correlation analysis reveals the quantitative range of all of these graph metrics and the relationships between them. Finally, we apply unsupervised machine learning to cluster real-world topologies into distinctive groups based on nine optimal graph metrics using K-means. It employs a two-step optimization process: optimal features are selected by maximizing feature uniqueness through principal component analysis, and the optimal number of clusters is determined by maximizing decision boundary distances via support vector machines. We conclude the analysis by providing guidance on how to use such clusters to select a diverse set of topologies for future studies. Topology Bench, openly available via Dataset 1 (https://zenodo.org/records/13921775) and Code 1 (https://github.com/TopologyBench), promotes accessibility, consistency, and reproducibility.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 1","pages":"7-27"},"PeriodicalIF":4.0,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810661","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}
Zhensheng Jia;Haipeng Zhang;Karthik Choutagunta;L. Alberto Campos
This paper presents a comprehensive overview of the emerging coherent passive optical network (CPON) technology and its role in the evolution of next-generation PON architectures. After reviewing the fundamental principles of traditional time-division multiplexed PON and tracking its development across successive standards, the unique benefits of applying coherent detection to PONs are examined. These include enhanced reach, increased split ratios, and improved overall network scalability. The paper explores various use cases, deployment scenarios, and architectural options for CPONs. Critical enabling technologies driving CPON development are analyzed, including upstream preamble design and burst-mode detection, techniques for transceiver cost reduction and implementation simplification, forward error correction, and out-of-band communication channels. Finally, the major industry standardization efforts currently underway to specify CPON across the physical, media access control, and system architecture layers are reviewed. By cohesively covering CPON’s evolution from core concepts to real-world specifications, this tutorial paper provides a definitive reference on this disruptive access network technology.
{"title":"Coherent passive optical network: applications, technologies, and specification development [Invited Tutorial]","authors":"Zhensheng Jia;Haipeng Zhang;Karthik Choutagunta;L. Alberto Campos","doi":"10.1364/JOCN.535200","DOIUrl":"https://doi.org/10.1364/JOCN.535200","url":null,"abstract":"This paper presents a comprehensive overview of the emerging coherent passive optical network (CPON) technology and its role in the evolution of next-generation PON architectures. After reviewing the fundamental principles of traditional time-division multiplexed PON and tracking its development across successive standards, the unique benefits of applying coherent detection to PONs are examined. These include enhanced reach, increased split ratios, and improved overall network scalability. The paper explores various use cases, deployment scenarios, and architectural options for CPONs. Critical enabling technologies driving CPON development are analyzed, including upstream preamble design and burst-mode detection, techniques for transceiver cost reduction and implementation simplification, forward error correction, and out-of-band communication channels. Finally, the major industry standardization efforts currently underway to specify CPON across the physical, media access control, and system architecture layers are reviewed. By cohesively covering CPON’s evolution from core concepts to real-world specifications, this tutorial paper provides a definitive reference on this disruptive access network technology.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 1","pages":"A71-A86"},"PeriodicalIF":4.0,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142797933","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}
Effective management of end-to-end 6G network services is crucial, with peak capacity requirements for 6G transport connections expected to exceed 1 Tb/s. As demand for high bandwidth rises, there is a growing necessity for high-capacity optical fiber links, including ultra-wideband (UWB) and multiple fiber links within the network. Scaling up to accommodate these demands, designing wavelength-selective switches (WSSs) for such networks significantly increases the port count. To tackle this issue, we propose various multi-granular optical node (MG-ON) architectures utilizing heterogeneous wavelength, waveband, and spatial switching. We evaluate these architectures’ performance against high-capacity wavelength division multiplexed (WDM) networks through various simulation parameters.
{"title":"Dynamic control, routing, and resource assignment in multi-granular optical node topologies combining wavelength, waveband, and spatial switching for 6G transport networks [Invited]","authors":"Varsha Lohani;Raul Munoz;Ramon Casellas;Lluis Gifre Renom;Carlos Manso;Ricard Vilalta;Ricardo Martinez","doi":"10.1364/JOCN.534789","DOIUrl":"https://doi.org/10.1364/JOCN.534789","url":null,"abstract":"Effective management of end-to-end 6G network services is crucial, with peak capacity requirements for 6G transport connections expected to exceed 1 Tb/s. As demand for high bandwidth rises, there is a growing necessity for high-capacity optical fiber links, including ultra-wideband (UWB) and multiple fiber links within the network. Scaling up to accommodate these demands, designing wavelength-selective switches (WSSs) for such networks significantly increases the port count. To tackle this issue, we propose various multi-granular optical node (MG-ON) architectures utilizing heterogeneous wavelength, waveband, and spatial switching. We evaluate these architectures’ performance against high-capacity wavelength division multiplexed (WDM) networks through various simulation parameters.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 1","pages":"A59-A70"},"PeriodicalIF":4.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142777853","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}
The use of optical access networks with aerial-deployed fiber for deriving maps of environmental temperature is investigated. Telecom operators have thousands of kilometers of deployed fiber to provide last-mile broadband services, which could be leveraged to extract temperature information with no additional cost since data are already available as part of the physical layer operations, administration, and maintenance (PLOAM) traffic. Here, it is shown how this information can be used to develop maps of environmental temperature as a method to complement present weather observation platforms. Preliminary experimental results with a G.984 passive optical network (PON) in operation show the feasibility of the technique.
{"title":"Leveraging PLOAM messaging for environmental temperature mapping in aerial-deployed time-division multiple access PONs","authors":"Borja Vidal;Cristian Salgado-Cazorla","doi":"10.1364/JOCN.530723","DOIUrl":"https://doi.org/10.1364/JOCN.530723","url":null,"abstract":"The use of optical access networks with aerial-deployed fiber for deriving maps of environmental temperature is investigated. Telecom operators have thousands of kilometers of deployed fiber to provide last-mile broadband services, which could be leveraged to extract temperature information with no additional cost since data are already available as part of the physical layer operations, administration, and maintenance (PLOAM) traffic. Here, it is shown how this information can be used to develop maps of environmental temperature as a method to complement present weather observation platforms. Preliminary experimental results with a G.984 passive optical network (PON) in operation show the feasibility of the technique.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 1","pages":"1-6"},"PeriodicalIF":4.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142777852","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 ability to provide worldwide communication coverage, satellite networks are drawing greater attention. The translucent optical payload enables the implementation of IP-over-WDM satellite optical networks (SONs), which can achieve great bandwidth capacity while providing the flexibility of IP routing. The rechargeable battery is the sole energy support for satellites in the eclipse region. Unrestrained discharge will accelerate battery aging and shorten the satellite operation period, causing extremely high expenditure costs. Satellite movement causes time-scheduled energy supply and traffic fluctuation, complicating the problem of energy consumption in IP-over-WDM SONs. This paper studies green traffic grooming (GTG) in IP-over-WDM SONs from the perspective of battery lifetime consumption (BLC). A grooming graph is designed to implement GTG with the physical impairment constraint in IP-over-WDM SONs, and battery-aware GTG (BA-GTG) and time-aware GTG (TA-GTG) are proposed by taking battery information and time information as prior knowledge. Numerical results indicate that BA-GTG and TA-GTG, especially the latter, can effectively reduce BLC. In addition, multiple link configurations are set in performance comparison to evaluate the effect of the physical impairment on battery efficiency in IP-over-WDM SONs.
卫星网络具有覆盖全球的通信能力，因此受到越来越多的关注。半透明光学有效载荷可实现 IP-over-WDM 卫星光网络（SON），在提供 IP 路由灵活性的同时，还能实现极大的带宽容量。可充电电池是日食区卫星的唯一能源支持。无节制放电会加速电池老化，缩短卫星运行周期，造成极高的支出成本。卫星移动会造成定时能源供应和流量波动，使 IP-over-WDM SON 的能耗问题更加复杂。本文从电池寿命消耗（BLC）的角度研究了 IP-over-WDM SON 中的绿色流量疏导（GTG）。通过将电池信息和时间信息作为先验知识，提出了电池感知 GTG（BA-GTG）和时间感知 GTG（TA-GTG）。数值结果表明，BA-GTG 和 TA-GTG，尤其是后者，能有效降低 BLC。此外，在性能比较中还设置了多种链路配置，以评估 IP-over-WDM SON 中物理损伤对电池效率的影响。
{"title":"Green traffic grooming in IP-over-WDM satellite optical networks","authors":"Yu Liu;Xin Li;Zhennan Zheng;Daixuan Li;Tianhao Liu;Feiyang Ruan;Chenyu Zhao;Shanguo Huang","doi":"10.1364/JOCN.539526","DOIUrl":"https://doi.org/10.1364/JOCN.539526","url":null,"abstract":"With the ability to provide worldwide communication coverage, satellite networks are drawing greater attention. The translucent optical payload enables the implementation of IP-over-WDM satellite optical networks (SONs), which can achieve great bandwidth capacity while providing the flexibility of IP routing. The rechargeable battery is the sole energy support for satellites in the eclipse region. Unrestrained discharge will accelerate battery aging and shorten the satellite operation period, causing extremely high expenditure costs. Satellite movement causes time-scheduled energy supply and traffic fluctuation, complicating the problem of energy consumption in IP-over-WDM SONs. This paper studies green traffic grooming (GTG) in IP-over-WDM SONs from the perspective of battery lifetime consumption (BLC). A grooming graph is designed to implement GTG with the physical impairment constraint in IP-over-WDM SONs, and battery-aware GTG (BA-GTG) and time-aware GTG (TA-GTG) are proposed by taking battery information and time information as prior knowledge. Numerical results indicate that BA-GTG and TA-GTG, especially the latter, can effectively reduce BLC. In addition, multiple link configurations are set in performance comparison to evaluate the effect of the physical impairment on battery efficiency in IP-over-WDM SONs.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"16 12","pages":"1275-1287"},"PeriodicalIF":4.0,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142736532","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}
Quality of transmission (QoT) prediction is a fundamental function in optical networks. It is typically embedded within a digital twin and used for operational tasks, including service establishment, service rerouting, and (per-channel or per-amplifier) power management to optimize the working point of services and hence to maximize their capacity. Inaccuracy in QoT prediction results in additional, unwanted design margins. A key contributor to QoT inaccuracy is the uncertain knowledge of fiber insertion loss, e.g., the attenuation due to connector losses at the beginning or at the end of each fiber span, as such loss cannot be directly monitored. Indeed, insertion losses drive the choice of the launch power in fiber spans, which in turn drive key physical effects, including the Kerr and stimulated Raman scattering (SRS) effects, which affect services’ QoT. It is thus important to estimate (and detect possibly anomalous) fiber insertion losses at each span. We thereby propose a novel active input refinement (AIR) technique using active probing to estimate insertion losses in C and C + L systems. Here, active probing consists of adjusting amplifier gains span by span to slightly alter SRS. The amount of adjustment must be sufficient to be measurable (such that insertion losses can be inferred from the measures) but small enough to have a negligible impact on running services in a live network. The method is validated by simulations on a European network with 30 optical multiplex sections (OMSs) in C and C + L configurations and by lab experiments on a C-band network, demonstrating that AIR significantly improves insertion loss estimation, network QoT optimization, and QoT prediction compared with other state-of-the-art monitoring techniques. This work underscores the critical role of accurate estimation of QoT inputs in enhancing optical network performance.
传输质量（QoT）预测是光网络的一项基本功能。它通常嵌入在数字孪生中，用于业务任务，包括业务建立、业务重路由和（每通道或每放大器）功率管理，以优化业务的工作点，从而最大限度地提高其容量。QoT 预测不准确会导致额外的、不必要的设计余量。造成 QoT 不准确的一个关键因素是对光纤插入损耗的不确定了解，例如，由于连接器损耗而在每条光纤的起始端或末端造成的衰减，因为这种损耗无法直接监测。事实上，插入损耗决定了光纤跨距中发射功率的选择，而发射功率又决定了关键的物理效应，包括影响服务 QoT 的克尔效应和受激拉曼散射（SRS）效应。因此，估算（并检测可能异常的）各跨距光纤插入损耗非常重要。因此，我们提出了一种新颖的主动输入细化（AIR）技术，利用主动探测来估算 C 和 C + L 系统中的插入损耗。在这里，主动探测包括逐跨调整放大器增益，以轻微改变 SRS。调整量必须足以进行测量（以便从测量结果中推断出插入损耗），但又要小到对实时网络中的运行服务影响可以忽略不计。该方法通过在一个欧洲网络上以 C 和 C + L 配置对 30 个光复用部分（OMS）进行模拟验证，并通过在 C 波段网络上进行实验室实验，证明与其他最先进的监控技术相比，AIR 能显著改善插入损耗估计、网络 QoT 优化和 QoT 预测。这项工作强调了准确估计 QoT 输入对提高光网络性能的关键作用。
{"title":"Digital-twin-based active input refinement for insertion loss estimation and QoT optimization in C and C + L networks","authors":"Xin Yang;Chenyu Sun;Gabriel Charlet;Massimo Tornatore;Yvan Pointurier","doi":"10.1364/JOCN.537734","DOIUrl":"https://doi.org/10.1364/JOCN.537734","url":null,"abstract":"Quality of transmission (QoT) prediction is a fundamental function in optical networks. It is typically embedded within a digital twin and used for operational tasks, including service establishment, service rerouting, and (per-channel or per-amplifier) power management to optimize the working point of services and hence to maximize their capacity. Inaccuracy in QoT prediction results in additional, unwanted design margins. A key contributor to QoT inaccuracy is the uncertain knowledge of fiber insertion loss, e.g., the attenuation due to connector losses at the beginning or at the end of each fiber span, as such loss cannot be directly monitored. Indeed, insertion losses drive the choice of the launch power in fiber spans, which in turn drive key physical effects, including the Kerr and stimulated Raman scattering (SRS) effects, which affect services’ QoT. It is thus important to estimate (and detect possibly anomalous) fiber insertion losses at each span. We thereby propose a novel active input refinement (AIR) technique using active probing to estimate insertion losses in C and C + L systems. Here, active probing consists of adjusting amplifier gains span by span to slightly alter SRS. The amount of adjustment must be sufficient to be measurable (such that insertion losses can be inferred from the measures) but small enough to have a negligible impact on running services in a live network. The method is validated by simulations on a European network with 30 optical multiplex sections (OMSs) in C and C + L configurations and by lab experiments on a C-band network, demonstrating that AIR significantly improves insertion loss estimation, network QoT optimization, and QoT prediction compared with other state-of-the-art monitoring techniques. This work underscores the critical role of accurate estimation of QoT inputs in enhancing optical network performance.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"16 12","pages":"1261-1274"},"PeriodicalIF":4.0,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142736533","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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