Yue Pang;Min Zhang;Yanli Liu;Xiangbin Li;Yidi Wang;Yahang Huan;Zhuo Liu;Jin Li;Danshi Wang
The optical network encompasses numerous devices and links, generating a significant volume of logs. Analyzing these logs is significant for network optimization, failure diagnosis, and health monitoring. However, the large-scale and diverse formats of optical network logs present several challenges, including the high cost and difficulty of manual processing, insufficient semantic understanding in existing analysis methods, and the strict requirements for data security and privacy. Generative artificial intelligence (GAI) with powerful language understanding and generation capabilities has the potential to address these challenges. Large language models (LLMs) as a concrete realization of GAI are well-suited for analyzing DCI logs, replacing human experts and enhancing accuracy. Additionally, LLMs enable intelligent interactions with network administrators, automating tasks and improving operational efficiency. Moreover, fine-tuning with open-source LLMs protects data privacy and enhances log analysis accuracy. Therefore, we introduce LLMs and propose a log analysis method with instruction tuning using LLaMA2 for log parsing, anomaly detection and classification, anomaly analysis, and report generation. Real log data extracted from the field-deployed network was used to design and construct instruction tuning datasets. We utilized the dataset for instruction tuning and demonstrated and evaluated the effectiveness of the proposed scheme. The results indicate that this scheme improves the performance of log analysis tasks, especially a 14% improvement in exact match rate for log parsing, a 13% improvement in F1-score for anomaly detection and classification, and a 23% improvement in usability for anomaly analysis, compared with the best baselines.
光网络包含众多设备和链路，会产生大量日志。分析这些日志对网络优化、故障诊断和健康监控意义重大。然而，光网络日志规模庞大、格式多样，这给我们带来了诸多挑战，包括人工处理成本高、难度大，现有分析方法对语义的理解不足，以及对数据安全和隐私的严格要求。具有强大语言理解和生成能力的生成人工智能（GAI）有望应对这些挑战。大型语言模型（LLMs）作为 GAI 的具体实现形式，非常适合分析 DCI 日志，可替代人类专家并提高准确性。此外，LLM 还能与网络管理员进行智能互动，实现任务自动化并提高运行效率。此外，使用开源 LLM 进行微调可保护数据隐私并提高日志分析的准确性。因此，我们引入了 LLM，并提出了一种使用 LLaMA2 进行指令调整的日志分析方法，用于日志解析、异常检测和分类、异常分析以及报告生成。从现场部署的网络中提取的真实日志数据被用于设计和构建指令调整数据集。我们利用该数据集进行了指令调整，并演示和评估了建议方案的有效性。结果表明，与最佳基线相比，该方案提高了日志分析任务的性能，特别是日志解析的精确匹配率提高了 14%，异常检测和分类的 F1 分数提高了 13%，异常分析的可用性提高了 23%。
{"title":"Large language model-based optical network log analysis using LLaMA2 with instruction tuning","authors":"Yue Pang;Min Zhang;Yanli Liu;Xiangbin Li;Yidi Wang;Yahang Huan;Zhuo Liu;Jin Li;Danshi Wang","doi":"10.1364/JOCN.527874","DOIUrl":"https://doi.org/10.1364/JOCN.527874","url":null,"abstract":"The optical network encompasses numerous devices and links, generating a significant volume of logs. Analyzing these logs is significant for network optimization, failure diagnosis, and health monitoring. However, the large-scale and diverse formats of optical network logs present several challenges, including the high cost and difficulty of manual processing, insufficient semantic understanding in existing analysis methods, and the strict requirements for data security and privacy. Generative artificial intelligence (GAI) with powerful language understanding and generation capabilities has the potential to address these challenges. Large language models (LLMs) as a concrete realization of GAI are well-suited for analyzing DCI logs, replacing human experts and enhancing accuracy. Additionally, LLMs enable intelligent interactions with network administrators, automating tasks and improving operational efficiency. Moreover, fine-tuning with open-source LLMs protects data privacy and enhances log analysis accuracy. Therefore, we introduce LLMs and propose a log analysis method with instruction tuning using LLaMA2 for log parsing, anomaly detection and classification, anomaly analysis, and report generation. Real log data extracted from the field-deployed network was used to design and construct instruction tuning datasets. We utilized the dataset for instruction tuning and demonstrated and evaluated the effectiveness of the proposed scheme. The results indicate that this scheme improves the performance of log analysis tasks, especially a 14% improvement in exact match rate for log parsing, a 13% improvement in F1-score for anomaly detection and classification, and a 23% improvement in usability for anomaly analysis, compared with the best baselines.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"16 11","pages":"1116-1132"},"PeriodicalIF":4.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142517897","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}
Some data center networks have already started to use optical circuit switching (OCS) with potential performance benefits, including high capacity, low latency, and energy efficiency. This paper addresses a switching network design to maximize the network radix, i.e., the number of terminals connected to the network under the condition that a specified number of identical switches with the size $N times N$ and the maximum admissible blocking probability are given. Previous work presented a two-stage twisted and folded Clos network (TF-Clos) with a blocking probability guarantee for OCS, which has a larger network radix than TF-Clos with a strict-sense non-blocking condition. Expanding the number of stages allows for enhancing the network radix. This paper proposes a model designing an OCS three-stage TF-Clos structure with a blocking probability guarantee to increase the network radix compared to the two-stage TF-Clos. We formulate the problem of obtaining the network configuration that maximizes the network radix as an optimization problem. We conduct an algorithm based on an exhaustive search to obtain a feasible solution satisfying the constraints of the optimization problem. This algorithm identifies the structure with the largest network radix in non-increasing order to avoid unnecessary searches. Numerical results show that the proposed model achieves a larger network radix than the two-stage model.
{"title":"Optical circuit switched three-stage twisted-folded Clos-network design model guaranteeing admissible blocking probability","authors":"Ryotaro Taniguchi;Takeru Inoue;Kazuya Anazawa;Eiji Oki","doi":"10.1364/JOCN.535282","DOIUrl":"https://doi.org/10.1364/JOCN.535282","url":null,"abstract":"Some data center networks have already started to use optical circuit switching (OCS) with potential performance benefits, including high capacity, low latency, and energy efficiency. This paper addresses a switching network design to maximize the network radix, i.e., the number of terminals connected to the network under the condition that a specified number of identical switches with the size \u0000<tex>$N times N$</tex>\u0000 and the maximum admissible blocking probability are given. Previous work presented a two-stage twisted and folded Clos network (TF-Clos) with a blocking probability guarantee for OCS, which has a larger network radix than TF-Clos with a strict-sense non-blocking condition. Expanding the number of stages allows for enhancing the network radix. This paper proposes a model designing an OCS three-stage TF-Clos structure with a blocking probability guarantee to increase the network radix compared to the two-stage TF-Clos. We formulate the problem of obtaining the network configuration that maximizes the network radix as an optimization problem. We conduct an algorithm based on an exhaustive search to obtain a feasible solution satisfying the constraints of the optimization problem. This algorithm identifies the structure with the largest network radix in non-increasing order to avoid unnecessary searches. Numerical results show that the proposed model achieves a larger network radix than the two-stage model.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"16 11","pages":"1104-1115"},"PeriodicalIF":4.0,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142518161","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}
Yongxin Xu;Xiaokai Guan;Wenqing Jiang;Xudong Wang;Weisheng Hu;Lilin Yi
End-to-end learning allows communication systems to achieve optimal performance compared with conventional blockwise structure design. By modeling the channel with neural networks and training the transmitter and receiver on this differentiable channel, the whole system can be jointly optimized. However, in existing schemes, channel modeling methods, such as the generative adversarial network and long short-term memory network, have complex architectures and cannot track channel changes, leading to less effective end-to-end learning. Meanwhile, the complexity of neural networks deployed at the transmitter and receiver is too high for practical applications. In this work, we propose an efficient and low-complexity end-to-end deep learning framework and experimentally validate it on a 100G passive optical network. It uses a noise adaptation network to model channel response and noise distribution and employs offline pretraining and online tracking training to improve the efficiency and accuracy of channel modeling. For the transmitter, it consists of a pattern-dependent look-up table (PDLUT) based on a neural network (NN-PDLUT) with a single convolutional layer. Further, the receiver is also an NN with a single convolutional layer; thus, the end-to-end signal processing is extremely simple. The experimental results show that end-to-end learning improves the receiver sensitivity by 0.85 and 1.59 dB compared with receiver-only equalization based on Volterra nonlinear equalization (VNLE) and joint equalization based on a PDLUT and a feed-forward equalizer, respectively. Moreover, the number of multiply–accumulate operations consumed by the transmitter and receiver in the end-to-end learning scheme is reduced by 75.7% compared with VNLE-based receiver-only equalization.
{"title":"Low-complexity end-to-end deep learning framework for 100G-PON","authors":"Yongxin Xu;Xiaokai Guan;Wenqing Jiang;Xudong Wang;Weisheng Hu;Lilin Yi","doi":"10.1364/JOCN.532742","DOIUrl":"https://doi.org/10.1364/JOCN.532742","url":null,"abstract":"End-to-end learning allows communication systems to achieve optimal performance compared with conventional blockwise structure design. By modeling the channel with neural networks and training the transmitter and receiver on this differentiable channel, the whole system can be jointly optimized. However, in existing schemes, channel modeling methods, such as the generative adversarial network and long short-term memory network, have complex architectures and cannot track channel changes, leading to less effective end-to-end learning. Meanwhile, the complexity of neural networks deployed at the transmitter and receiver is too high for practical applications. In this work, we propose an efficient and low-complexity end-to-end deep learning framework and experimentally validate it on a 100G passive optical network. It uses a noise adaptation network to model channel response and noise distribution and employs offline pretraining and online tracking training to improve the efficiency and accuracy of channel modeling. For the transmitter, it consists of a pattern-dependent look-up table (PDLUT) based on a neural network (NN-PDLUT) with a single convolutional layer. Further, the receiver is also an NN with a single convolutional layer; thus, the end-to-end signal processing is extremely simple. The experimental results show that end-to-end learning improves the receiver sensitivity by 0.85 and 1.59 dB compared with receiver-only equalization based on Volterra nonlinear equalization (VNLE) and joint equalization based on a PDLUT and a feed-forward equalizer, respectively. Moreover, the number of multiply–accumulate operations consumed by the transmitter and receiver in the end-to-end learning scheme is reduced by 75.7% compared with VNLE-based receiver-only equalization.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"16 11","pages":"1093-1103"},"PeriodicalIF":4.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142450921","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 DWDM transmission offers enhanced wavelength/spectrum parallelism, the capacity of optical networks has been substantially increased. Due to the theoretical capacity limit of C-band transmission over single-mode fibers, research into new frequency bands and parallel fibers has become very active. However, the hardware scale of current optical cross-connect nodes will explode with greater wavelength/spectrum and spatial parallelism. Three optical node/network architectures are presented in this paper that take advantage of one or both of these parallelism technologies. These architectures will provide a baseline for cost-effective and bandwidth-abundant future optical networks based on massive parallelism.
由于 DWDM 传输提供了更强的波长/频谱并行性，光网络的容量得到了大幅提高。由于单模光纤 C 波段传输的理论容量有限，对新频段和并行光纤的研究变得非常活跃。然而，随着波长/频谱和空间并行性的提高，目前光交叉连接节点的硬件规模将出现爆炸式增长。本文介绍了三种利用一种或两种并行技术的光节点/网络架构。这些架构将为未来基于大规模并行性的高成本效益和带宽充裕的光网络提供基线。
{"title":"Optical networking that exploits massive wavelength/spectrum and spatial parallelisms","authors":"Hiroshi Hasegawa","doi":"10.1364/JOCN.532594","DOIUrl":"https://doi.org/10.1364/JOCN.532594","url":null,"abstract":"As DWDM transmission offers enhanced wavelength/spectrum parallelism, the capacity of optical networks has been substantially increased. Due to the theoretical capacity limit of C-band transmission over single-mode fibers, research into new frequency bands and parallel fibers has become very active. However, the hardware scale of current optical cross-connect nodes will explode with greater wavelength/spectrum and spatial parallelism. Three optical node/network architectures are presented in this paper that take advantage of one or both of these parallelism technologies. These architectures will provide a baseline for cost-effective and bandwidth-abundant future optical networks based on massive parallelism.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"16 11","pages":"H27-H39"},"PeriodicalIF":4.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443146","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 lack of standards in the performance evaluation of new resource allocation algorithms in multicore fiber elastic optical networks (MCF-EONs) compromises the fairness when comparing them with the state of the art. This paper reviews the different transmission parameters, network parameters, performance metrics, and baselines used by the recent proposals to build a framework for future benchmarking of such algorithms according to the nature of the network operation, whether static or dynamic. This framework aims to provide standards regarding evaluation criteria, scenarios, and performance metrics, as well as recommendations concerning technology advances to promote methodology and reproducibility in further related studies.
{"title":"Benchmarking framework for resource allocation algorithms in multicore fiber elastic optical networks","authors":"Juan Pinto-Rios;Barbara Dumas Feris;Christofer Vasquez;Gabriel Saavedra;Danilo Borquez-Paredes;Nicolas Jara;Ricardo Olivares;Saquib Amjad;Ariel Leiva;Carmen Mas-Machuca","doi":"10.1364/JOCN.534257","DOIUrl":"https://doi.org/10.1364/JOCN.534257","url":null,"abstract":"The lack of standards in the performance evaluation of new resource allocation algorithms in multicore fiber elastic optical networks (MCF-EONs) compromises the fairness when comparing them with the state of the art. This paper reviews the different transmission parameters, network parameters, performance metrics, and baselines used by the recent proposals to build a framework for future benchmarking of such algorithms according to the nature of the network operation, whether static or dynamic. This framework aims to provide standards regarding evaluation criteria, scenarios, and performance metrics, as well as recommendations concerning technology advances to promote methodology and reproducibility in further related studies.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"16 11","pages":"G11-G27"},"PeriodicalIF":4.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142438501","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}
Growing capacity requirements are leading to the deployment of multiple fibers in each optical network link. Even though deploying state-of-the-art multi-fiber network architectures with stacked and independent fiber layers simplifies network design and control, spectrum can be used more efficiently if the optical-network nodes allow fiber layers to be interconnected, i.e., if the so-called lane change is enabled. Unfortunately, lane change in high-degree optical nodes requires wavelength selective switches (WSSs) with a high number of ports, which is prohibitively costly or even unfeasible with current WSS technology. Instead, lane change in low-degree optical nodes can be enabled at no extra cost, using WSS ports that are otherwise left empty. In this study, we describe our proposal for a multi-fiber network with partial lane-change capabilities and perform a simulative study to identify the advantages of this architecture, as well as discuss the emerging resource allocation challenges associated with it. We demonstrate that, by enabling lane change in degree-2 nodes, we can increase network throughput by 3% and restore 5%–8% more traffic in the case of single- and double-link failures at no additional equipment cost.
{"title":"Zero-cost upgrade to a multi-fiber network with partial lane-change capabilities","authors":"Oleg Karandin;Francesco Musumeci;Gabriel Charlet;Yvan Pointurier;Massimo Tornatore","doi":"10.1364/JOCN.533906","DOIUrl":"https://doi.org/10.1364/JOCN.533906","url":null,"abstract":"Growing capacity requirements are leading to the deployment of multiple fibers in each optical network link. Even though deploying state-of-the-art multi-fiber network architectures with stacked and independent fiber layers simplifies network design and control, spectrum can be used more efficiently if the optical-network nodes allow fiber layers to be interconnected, i.e., if the so-called lane change is enabled. Unfortunately, lane change in high-degree optical nodes requires wavelength selective switches (WSSs) with a high number of ports, which is prohibitively costly or even unfeasible with current WSS technology. Instead, lane change in low-degree optical nodes can be enabled at no extra cost, using WSS ports that are otherwise left empty. In this study, we describe our proposal for a multi-fiber network with partial lane-change capabilities and perform a simulative study to identify the advantages of this architecture, as well as discuss the emerging resource allocation challenges associated with it. We demonstrate that, by enabling lane change in degree-2 nodes, we can increase network throughput by 3% and restore 5%–8% more traffic in the case of single- and double-link failures at no additional equipment cost.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"16 11","pages":"H18-H26"},"PeriodicalIF":4.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142438447","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}
In this paper, we propose an original adaptive neural network equalizer (NNE) algorithm named SkipNet, which is suitable for rapid training on a packet-by-packet basis for burst-mode non-linear equalization in upstream PON transmission. SkipNet uses the simple LMS algorithm and avoids complex neural network training algorithms such as backpropagation and mini-batch training. We demonstrate SkipNet on captured continuous mode 100 Gbit/s PAM4 signals using an SOA preamplifier to achieve the challenging 29 dB PON optical loss budget. The adaptive SkipNet equalizer is shown to overcome combinations of severe SOA patterning effects and fiber dispersion impairments to achieve ${gt}{29};{rm dB}$ dynamic range back-to-back and ${gt}{22.9};{rm dB}$ dynamic range for up to 81.6 ps/nm accumulated dispersion. It can adapt in as little as 250 training symbols to each impairment scenario, which is equivalent to existing FFE/DFE solutions, while matching the non-linear performance of previously proposed static NNE solutions. To the best of our knowledge, SkipNet is the first ever adaptive NNE framework that can realistically be trained and adapted on a packet-by-packet basis and within strict PON packet preamble lengths.
本文提出了一种名为 "SkipNet "的独创自适应神经网络均衡器（NNE）算法，适用于在上游 PON 传输中逐个数据包快速训练突发模式非线性均衡。SkipNet 使用简单的 LMS 算法，避免了复杂的神经网络训练算法，如反向传播和迷你批量训练。我们使用 SOA 前置放大器在捕获的连续模式 100 Gbit/s PAM4 信号上演示了 SkipNet，以实现具有挑战性的 29 dB PON 光损耗预算。研究表明，自适应 SkipNet 均衡器能够克服严重的 SOA 图案效应和光纤色散损伤，从而在高达 81.6 ps/nm 的累积色散条件下实现${{29}/;{/rm dB}$的背靠背动态范围和${{22.9}/;{/rm dB}$的动态范围。它能在短短 250 个训练符号内适应每种损伤情况，这与现有的 FFE/DFE 解决方案相当，同时与之前提出的静态 NNE 解决方案的非线性性能相匹配。据我们所知，SkipNet 是有史以来第一个自适应 NNE 框架，可以在严格的 PON 数据包前导码长度范围内逐个数据包进行实际训练和调整。
{"title":"SkipNet: an adaptive neural network equalization algorithm for future passive optical networking","authors":"Stephen L. Murphy;Paul D. Townsend;Cleitus Antony","doi":"10.1364/JOCN.528490","DOIUrl":"10.1364/JOCN.528490","url":null,"abstract":"In this paper, we propose an original adaptive neural network equalizer (NNE) algorithm named SkipNet, which is suitable for rapid training on a packet-by-packet basis for burst-mode non-linear equalization in upstream PON transmission. SkipNet uses the simple LMS algorithm and avoids complex neural network training algorithms such as backpropagation and mini-batch training. We demonstrate SkipNet on captured continuous mode 100 Gbit/s PAM4 signals using an SOA preamplifier to achieve the challenging 29 dB PON optical loss budget. The adaptive SkipNet equalizer is shown to overcome combinations of severe SOA patterning effects and fiber dispersion impairments to achieve \u0000<tex>${gt}{29};{rm dB}$</tex>\u0000 dynamic range back-to-back and \u0000<tex>${gt}{22.9};{rm dB}$</tex>\u0000 dynamic range for up to 81.6 ps/nm accumulated dispersion. It can adapt in as little as 250 training symbols to each impairment scenario, which is equivalent to existing FFE/DFE solutions, while matching the non-linear performance of previously proposed static NNE solutions. To the best of our knowledge, SkipNet is the first ever adaptive NNE framework that can realistically be trained and adapted on a packet-by-packet basis and within strict PON packet preamble lengths.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"16 11","pages":"1082-1092"},"PeriodicalIF":4.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10712641","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141800990","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}
This paper investigates the practical scalability of wavelength selective switching technology for the emerging multi-band and space-division-multiplexed (SDM) networks. Wavelength selective switching architectures are introduced for multi-band SDM networks. The switching capacity is analyzed for both weakly coupled and strongly coupled SDM networks. Key bottlenecks for scaling up toward multi-band and more spatial modes are identified. Contrary to the conventional view that liquid crystal on silicon (LCOS) was the only technological obstacle, the manufacturability of free-space optics with high numerical apertures and constraints on the optical dimensions also brought significant challenges for the development of highly integrated wavelength selective switches for multi-band SDM networks.
{"title":"Scaling wavelength selective switches for multi-band and space-division-multiplexed networks","authors":"Haoyu Wei;Weixin Chen;Haining Yang","doi":"10.1364/JOCN.531337","DOIUrl":"https://doi.org/10.1364/JOCN.531337","url":null,"abstract":"This paper investigates the practical scalability of wavelength selective switching technology for the emerging multi-band and space-division-multiplexed (SDM) networks. Wavelength selective switching architectures are introduced for multi-band SDM networks. The switching capacity is analyzed for both weakly coupled and strongly coupled SDM networks. Key bottlenecks for scaling up toward multi-band and more spatial modes are identified. Contrary to the conventional view that liquid crystal on silicon (LCOS) was the only technological obstacle, the manufacturability of free-space optics with high numerical apertures and constraints on the optical dimensions also brought significant challenges for the development of highly integrated wavelength selective switches for multi-band SDM networks.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"16 11","pages":"H9-H17"},"PeriodicalIF":4.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397380","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}
This paper reviews and analyzes multicore-fiber technologies in the context of submarine networks. As global/transcontinental capacity continues to grow at a large and steady pace, the subsea industry is challenged to deliver technologies that provide large-capacity networks in a faster, greener, and cost-effective fashion. Multicore fiber has been considered as a serious candidate for next-generation systems with the ability to maintain standard cable size at large core counts. This paper analyzes the technoeconomics of next-generation submarine systems including variables such as equipment size versus marine cost and other critical elements (not analyzed before, to our knowledge) for submarine system implementation. In this context, this paper also analyzes the state-of-the-art of multicore subsystems and components and discusses their roadmaps, requirements, and evolution toward the realization of a multicore ecosystem for next-generation SDM systems.
{"title":"Multicore-fiber submarine systems","authors":"Eduardo F. Mateo","doi":"10.1364/JOCN.532163","DOIUrl":"https://doi.org/10.1364/JOCN.532163","url":null,"abstract":"This paper reviews and analyzes multicore-fiber technologies in the context of submarine networks. As global/transcontinental capacity continues to grow at a large and steady pace, the subsea industry is challenged to deliver technologies that provide large-capacity networks in a faster, greener, and cost-effective fashion. Multicore fiber has been considered as a serious candidate for next-generation systems with the ability to maintain standard cable size at large core counts. This paper analyzes the technoeconomics of next-generation submarine systems including variables such as equipment size versus marine cost and other critical elements (not analyzed before, to our knowledge) for submarine system implementation. In this context, this paper also analyzes the state-of-the-art of multicore subsystems and components and discusses their roadmaps, requirements, and evolution toward the realization of a multicore ecosystem for next-generation SDM systems.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"16 11","pages":"H1-H8"},"PeriodicalIF":4.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397506","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}
Caio Santos;Abdelrahmane Moawad;Behnam Shariati;Robert Emmerich;Pooyan Safari;Colja Schubert;Johannes K. Fischer
Due to the scarcity of diverse and well-organized public datasets, individual research organizations are often forced to develop and utilize their own datasets. However, the utilization of machine learning (ML) models in optical communications and networks heavily depends on the existence of high-quality datasets, especially covering the various parameters to be optimized in wavelength-division multiplexing (WDM) systems. In this work, we present a public dataset for developing and testing ML models. The dataset is developed in a laboratory setting and includes 12,672 samples including data points with different modulation formats, symbol rates, distances, WDM channel allocation profiles, etc. Each data point offers more than 60 features, revealing almost every aspect of the transmission setup. Moreover, we provide optical spectra of the entire C-band as well as a constellation diagram of the channel under test for all the data points. The diversity and extensiveness of the dataset alongside a well-structured document would allow plenty of use-cases and studies to be carried out covering quality of transmission (QoT) studies, optical spectrum analysis, constellation diagram modeling, digital twin evaluation, etc. Similar to our previous efforts, the current dataset aims to facilitate collaboration by offering a way for fair comparison of research outcomes in data analysis within the domain of optical communication systems.
由于缺乏种类繁多、组织有序的公共数据集，各个研究机构往往不得不开发和利用自己的数据集。然而，机器学习（ML）模型在光通信和网络中的应用在很大程度上依赖于高质量数据集的存在，尤其是涵盖波分复用（WDM）系统中需要优化的各种参数的数据集。在这项工作中，我们提出了一个用于开发和测试 ML 模型的公共数据集。该数据集是在实验室环境中开发的，包含 12672 个样本，包括不同调制格式、符号率、距离、波分复用信道分配情况等数据点。每个数据点提供 60 多个特征，揭示了传输设置的几乎所有方面。此外，我们还为所有数据点提供了整个 C 波段的光学光谱以及被测信道的星座图。数据集的多样性和广泛性以及结构良好的文档将允许开展大量的用例和研究，包括传输质量（QoT）研究、光学频谱分析、星座图建模、数字孪生评估等。与我们之前的工作类似，当前的数据集旨在通过提供一种公平比较光通信系统领域内数据分析研究成果的方法来促进合作。
{"title":"Experimental dataset for developing and testing ML models in optical communication systems","authors":"Caio Santos;Abdelrahmane Moawad;Behnam Shariati;Robert Emmerich;Pooyan Safari;Colja Schubert;Johannes K. Fischer","doi":"10.1364/JOCN.531788","DOIUrl":"https://doi.org/10.1364/JOCN.531788","url":null,"abstract":"Due to the scarcity of diverse and well-organized public datasets, individual research organizations are often forced to develop and utilize their own datasets. However, the utilization of machine learning (ML) models in optical communications and networks heavily depends on the existence of high-quality datasets, especially covering the various parameters to be optimized in wavelength-division multiplexing (WDM) systems. In this work, we present a public dataset for developing and testing ML models. The dataset is developed in a laboratory setting and includes 12,672 samples including data points with different modulation formats, symbol rates, distances, WDM channel allocation profiles, etc. Each data point offers more than 60 features, revealing almost every aspect of the transmission setup. Moreover, we provide optical spectra of the entire C-band as well as a constellation diagram of the channel under test for all the data points. The diversity and extensiveness of the dataset alongside a well-structured document would allow plenty of use-cases and studies to be carried out covering quality of transmission (QoT) studies, optical spectrum analysis, constellation diagram modeling, digital twin evaluation, etc. Similar to our previous efforts, the current dataset aims to facilitate collaboration by offering a way for fair comparison of research outcomes in data analysis within the domain of optical communication systems.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"16 11","pages":"G1-G10"},"PeriodicalIF":4.0,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142377114","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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