Journal of Optical Communications and Networking最新文献_第3页

Large language model-based optical network log analysis using LLaMA2 with instruction tuning 使用带有指令调整功能的 LLaMA2 进行基于大型语言模型的光网络日志分析

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2024-10-24 DOI: 10.1364/JOCN.527874

Yue Pang;Min Zhang;Yanli Liu;Xiangbin Li;Yidi Wang;Yahang Huan;Zhuo Liu;Jin Li;Danshi Wang

{"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}

引用次数: 0

Optical circuit switched three-stage twisted-folded Clos-network design model guaranteeing admissible blocking probability 保证可接受阻塞概率的光路交换式三级扭曲折叠 Clos 网络设计模型

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2024-10-22 DOI: 10.1364/JOCN.535282

Ryotaro Taniguchi;Takeru Inoue;Kazuya Anazawa;Eiji Oki

{"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}

引用次数: 0

Low-complexity end-to-end deep learning framework for 100G-PON 面向 100G-PON 的低复杂度端到端深度学习框架

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2024-10-18 DOI: 10.1364/JOCN.532742

Yongxin Xu;Xiaokai Guan;Wenqing Jiang;Xudong Wang;Weisheng Hu;Lilin Yi

{"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}

引用次数: 0

Optical networking that exploits massive wavelength/spectrum and spatial parallelisms 利用大规模波长/频谱和空间并行性的光网络技术

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2024-10-16 DOI: 10.1364/JOCN.532594

Hiroshi Hasegawa

引用次数: 0

Benchmarking framework for resource allocation algorithms in multicore fiber elastic optical networks 多核光纤弹性光网络资源分配算法基准框架

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2024-10-15 DOI: 10.1364/JOCN.534257

Juan Pinto-Rios;Barbara Dumas Feris;Christofer Vasquez;Gabriel Saavedra;Danilo Borquez-Paredes;Nicolas Jara;Ricardo Olivares;Saquib Amjad;Ariel Leiva;Carmen Mas-Machuca

引用次数: 0

Zero-cost upgrade to a multi-fiber network with partial lane-change capabilities 零成本升级为具有部分变道功能的多光纤网络

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2024-10-15 DOI: 10.1364/JOCN.533906

Oleg Karandin;Francesco Musumeci;Gabriel Charlet;Yvan Pointurier;Massimo Tornatore

{"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}

引用次数: 0

SkipNet: an adaptive neural network equalization algorithm for future passive optical networking SkipNet：未来无源光网络的自适应神经网络均衡算法

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2024-10-09 DOI: 10.1364/JOCN.528490

Stephen L. Murphy;Paul D. Townsend;Cleitus Antony

{"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}

引用次数: 0

Scaling wavelength selective switches for multi-band and space-division-multiplexed networks 为多频带和空分多路复用网络扩展波长选择开关

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2024-10-08 DOI: 10.1364/JOCN.531337

Haoyu Wei;Weixin Chen;Haining Yang

引用次数: 0

Multicore-fiber submarine systems 多芯光纤潜艇系统

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2024-10-08 DOI: 10.1364/JOCN.532163

Eduardo F. Mateo

引用次数: 0

Experimental dataset for developing and testing ML models in optical communication systems 用于开发和测试光通信系统 ML 模型的实验数据集

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2024-10-04 DOI: 10.1364/JOCN.531788

Caio Santos;Abdelrahmane Moawad;Behnam Shariati;Robert Emmerich;Pooyan Safari;Colja Schubert;Johannes K. Fischer

{"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}

引用次数: 0