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Multi-span optical power spectrum prediction using cascaded learning with one-shot end-to-end measurement 利用级联学习和一次端到端测量进行多跨度光功率谱预测
IF 4 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-11-07 DOI: 10.1364/JOCN.533634
Zehao Wang;Yue-Kai Huang;Shaobo Han;Daniel Kilper;Tingjun Chen
Scalable methods for optical transmission performance prediction using machine learning (ML) are studied in metro reconfigurable optical add-drop multiplexer (ROADM) networks. A cascaded learning framework is introduced to encompass the use of cascaded component models for end-to-end (E2E) optical path prediction augmented with different combinations of E2E performance data and models. Additional E2E optical path data and models are used to reduce the prediction error accumulation in the cascade. Off-line training (pre-trained prior to deployment) and transfer learning are used for component-level erbium-doped fiber amplifier (EDFA) gain models to ensure scalability. Considering channel power prediction, we show that the data collection process of the pre-trained EDFA model can be reduced to only 5% of the original training set using transfer learning. We evaluate the proposed method under three different topologies with field deployed fibers and achieve a mean absolute error of 0.16 dB with a single (one-shot) E2E measurement on the deployed 6-span system with 12 EDFAs.
在城域可重构光分插复用器(ROADM)网络中研究了利用机器学习(ML)进行光传输性能预测的可扩展方法。引入了级联学习框架,将级联组件模型用于端到端(E2E)光路径预测,并使用不同的 E2E 性能数据和模型组合进行增强。额外的 E2E 光路径数据和模型用于减少级联中累积的预测误差。为确保可扩展性,对元件级掺铒光纤放大器(EDFA)增益模型采用了离线训练(部署前的预训练)和迁移学习。考虑到信道功率预测,我们表明,使用迁移学习,预训练 EDFA 模型的数据收集过程可减少到原始训练集的 5%。我们在现场部署光纤的三种不同拓扑结构下评估了所提出的方法,并在部署了 12 个 EDFA 的 6 跨系统上进行了单次(一次)E2E 测量,平均绝对误差为 0.16 dB。
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引用次数: 0
Ultra-high-capacity band and space division multiplexing backbone EONs: multi-core versus multi-fiber 超大容量频带和空分复用主干 EON:多核与多光纤
IF 4 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-11-06 DOI: 10.1364/JOCN.533086
Farhad Arpanaei;Mahdi Ranjbar Zefreh;Carlos Natalino;Piotr Lechowicz;Shuangyi Yan;Jose M. Rivas-Moscoso;Oscar Gonzalez de Dios;Juan Pedro Fernandez-Palacios;Hami Rabbani;Maite Brandt-Pearce;Alfonso Sanchez-Macian;Jose Alberto Hernandez;David Larrabeiti;Paolo Monti
Both multi-band and space division multiplexing (SDM) independently represent cost-effective approaches for next-generation optical backbone networks, particularly as data exchange between core data centers reaches the petabit-per-second scale. This paper focuses on different strategies for implementing band and SDM elastic optical network (BSDM EON) technology and analyzes the total network capacity of three sizes of backbone metro-core networks: ultra-long-, long-, and medium-distance networks related to the United States, Japan, and Spain, respectively. Two BSDM strategies are considered, namely, multi-core fibers (MCFs) and BSDM based on standard single-mode fiber (SSMF) bundles of multi-fiber pairs (BuMFPs). For MCF-based BSDM, we evaluated the performance of four manufactured trench-assisted weakly coupled (TAWC) MCFs with 4, 7, 13, and 19 cores. Simulation results reveal that, in the regime of ultra-low (UL) loss and inter-core crosstalk (ICXT), MCF-based throughput can be up to 14% higher than SSMF BuMFP-based BSDM when the core pitch exceeds 43 µm and the loss coefficient is lower than that of standard single-mode fibers. However, increasing the number of cores with (non-)standard cladding diameters, UL loss, and ICXT coefficient is not beneficial. As core counts increase up to 13 for non-standard cladding diameters (${lt}230;{unicode{x00B5}{rm m}}$), the core pitch and loss coefficient also increase, leading to degraded performance of MCF-based BSDM compared to SSMF BuMFP-based BSDM. The results indicate that, in scenarios with 19 MFPs, SSFM BuMFP-based BSDM outperforms 19-core MCF-based scenarios, increasing the throughput by 55% to 73%, from medium-backbone networks to ultra-long ones.
多频段和空分复用(SDM)都是下一代光骨干网的经济有效的独立方法,尤其是当核心数据中心之间的数据交换达到每秒千万比特级别时。本文重点讨论了实施频带和 SDM 弹性光网络(BSDM EON)技术的不同策略,并分析了三种规模的骨干城域核心网络的总网络容量:分别与美国、日本和西班牙相关的超长距、长距和中距网络。考虑了两种 BSDM 策略,即多芯光纤(MCF)和基于标准单模光纤(SSMF)的多光纤对束(BuMFP)BSDM。对于基于 MCF 的 BSDM,我们评估了四种制造的沟槽辅助弱耦合(TAWC)MCF 的性能,它们分别有 4 芯、7 芯、13 芯和 19 芯。仿真结果表明,在超低(UL)损耗和纤芯间串扰(ICXT)情况下,当纤芯间距超过 43 µm 且损耗系数低于标准单模光纤时,基于 MCF 的吞吐量最多可比基于 SSMF BuMFP 的 BSDM 高 14%。然而,增加具有(非)标准包层直径、UL 损耗和 ICXT 系数的纤芯数量并无益处。当非标准包层直径(${unicode{x00B5}{rm m}}$)的纤芯数增加到 13 个时,纤芯间距和损耗系数也会增加,从而导致基于 MCF 的 BSDM 性能比基于 SSMF BuMFP 的 BSDM 性能下降。结果表明,在有 19 个 MFP 的情况下,基于 SSFM BuMFP 的 BSDM 优于基于 19 核 MCF 的情况,从中型骨干网络到超长网络,吞吐量提高了 55% 到 73%。
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引用次数: 0
Polarity management of multicore fiber-based optical devices in unidirectional and bidirectional spatial channel networks 单向和双向空间信道网络中基于多芯光纤的光设备极性管理
IF 4 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-11-05 DOI: 10.1364/JOCN.532960
Masahiko Jinno;Rika Tahara;Kyosuke Nakada;Takuma Izumi;Kako Matsumoto
Uncoupled multicore fibers (MCFs) are expected to be the first to be commercially deployed due to their high compatibility with existing single-mode fiber technologies. Since MCFs have a 3D shape, they generally exhibit connection polarity. Thus, optical devices based on MCFs also generally have polarity, which will complicate the core resource assignment and end-to-end core connections in future MCF-based spatial channel networks (SCNs). In this paper, we first discuss the polarity of MCF-based optical devices (MODs) such as MCF patch cords, spatial multiplexers (SMUXs), core selective switches (CSSs), and core selectors (CSs). We then propose a definition for global core numbers in a two-MCF unidirectional (2MCF-UD) SCN and a single-MCF bidirectional (1MCF-BD) SCN. We also propose a method for managing the polarity of MODs and correctly connecting cores end-to-end. To verify the effectiveness of the proposed global core numbering and polarity management method for MODs, testbeds emulating a 2MCF-UD SCN and a 1MCF-BD SCN are constructed using prototype CSS, CS, and SMUX devices. By using light with different optical frequencies as input and observing the output spectrum, we confirm that the spatial channel specified by the global core number is established correctly end-to-end in the SCN if the polarity of the MODs is set correctly.
无耦合多芯光纤(MCF)与现有的单模光纤技术具有很高的兼容性,因此有望率先投入商业应用。由于 MCF 具有三维形状,因此通常表现出连接极性。因此,基于 MCF 的光设备通常也具有极性,这将使未来基于 MCF 的空间信道网络(SCN)中的核心资源分配和端到端核心连接变得更加复杂。本文首先讨论了基于 MCF 的光设备(MOD)的极性,如 MCF 跳线、空间多路复用器(SMUX)、核心选择开关(CSS)和核心选择器(CS)。然后,我们提出了双 MCF 单向 SCN(2MCF-UD)和单 MCF 双向 SCN(1MCF-BD)中全局核心数的定义。我们还提出了一种管理 MOD 极性和端到端正确连接内核的方法。为了验证所提出的 MOD 全局核心编号和极性管理方法的有效性,我们使用原型 CSS、CS 和 SMUX 设备构建了模拟 2MCF-UD SCN 和 1MCF-BD SCN 的测试平台。通过使用不同光频的光作为输入并观察输出光谱,我们证实,如果 MOD 的极性设置正确,全局核编号指定的空间信道就能在 SCN 中端到端正确建立。
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引用次数: 0
Probabilistic path computation and frequency assignment to mitigate spectral fragmentation in elastic optical networks 通过概率路径计算和频率分配缓解弹性光网络中的频谱碎片问题
IF 4 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-11-04 DOI: 10.1364/JOCN.538610
Francois Moore;Andrea Fumagalli
Management of spectrum fragmentation in optical transport networks typically requires after the fact defragmentation. This paper proposes a probabilistic approach that mitigates the creation of fragmentation by reducing spectral waste and increasing the expected number of allowable additional lightpaths. The proposed approach is simulated and compared against both first fit as well as fragmentation aware spectrum assignment methods, and the comparison results are provided.
光传输网络中的频谱碎片管理通常需要进行事后碎片整理。本文提出了一种概率方法,通过减少频谱浪费和增加可允许的额外光路的预期数量来缓解碎片的产生。本文对所提出的方法进行了仿真,并将其与首次拟合以及碎片感知频谱分配方法进行了比较,同时提供了比较结果。
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引用次数: 0
Layout design of densest weakly coupled multi-core fibers to minimize the network blocking rate 最密集弱耦合多芯光纤的布局设计,最大限度降低网络阻塞率
IF 4 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-11-01 DOI: 10.1364/JOCN.531706
Yuya Seki;Yosuke Tanigawa;Yusuke Hirota;Hideki Tode
The suppression of inter-core crosstalk (IC-XT) that affects each lightpath is crucial for resource allocation in space-division multiplexing elastic optical networks (SDM-EONs) with multi-core fibers (MCFs). Resource allocation approaches that limit the simultaneous use of adjacent cores in the same frequency band to the MCFs composing each lightpath have been widely adopted to suppress IC-XT. However, in principle, such methods are inefficient because they cannot fully utilize all cores. This study examines the core density from the perspective of the core layout in weakly coupled MCFs and the IC-XT suppression requirement. The densest MCF layout maximizes the network capacity while restricting the amount of IC-XT within the tolerance threshold for each lightpath. Specifically, we propose an XT-free condition, maintaining the IC-XT to each lightpath within the acceptable tolerance level. In addition, we evaluated numerous MCFs that satisfy or do not satisfy the XT-free condition with various network topologies and cladding diameters. This evaluation also validates the IC-XT reduction performance of the proposed framework compared with that of the conventional resource-allocation approach. Here, we incorporate our indirect IC-XT calculation method that affects lightpaths from other cores via its nearest cores, which was overlooked in the resource allocation problem. Based on these comprehensive examinations, we propose a method to determine the densest core layout for a given network topology and route and modulation format selection algorithm.
抑制影响每个光路的纤芯间串扰(IC-XT)对于使用多纤芯光纤(MCF)的空间分复用弹性光网络(SDM-EON)的资源分配至关重要。为了抑制 IC-XT,人们广泛采用了资源分配方法,即限制构成每个光路的 MCF 同时使用同一频段的相邻内核。然而,从原理上讲,这种方法效率低下,因为它们无法充分利用所有内核。本研究从弱耦合 MCF 的磁芯布局和 IC-XT 抑制要求的角度研究了磁芯密度。最密集的 MCF 布局既能最大限度地提高网络容量,又能将每个光路的 IC-XT 量限制在容差阈值内。具体来说,我们提出了无 XT 条件,将每个光路的 IC-XT 量保持在可接受的容差范围内。此外,我们还评估了各种网络拓扑结构和包层直径下满足或不满足无 XT 条件的众多 MCF。与传统的资源分配方法相比,该评估还验证了拟议框架的 IC-XT 减少性能。在这里,我们纳入了我们的间接 IC-XT 计算方法,该方法通过其最近的内核影响来自其他内核的光路,而这在资源分配问题中被忽视了。在这些综合研究的基础上,我们提出了一种方法,用于确定给定网络拓扑和路由及调制格式选择算法下的最密集核心布局。
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引用次数: 0
Optical Networking Gym: an open-source toolkit for resource assignment problems in optical networks 光网络健身房:用于解决光网络资源分配问题的开源工具包
IF 4 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-10-31 DOI: 10.1364/JOCN.532850
Carlos Natalino;Talles Magalhaes;Farhad Arpanaei;Fabricio R. L. Lobato;Joao C. W. A. Costa;Jose Alberto Hernandez;Paolo Monti
The dynamic provisioning of optical network services requires algorithms to find a suitable solution given the specific service requirements and the current network state. These algorithms are usually evaluated using a software simulator developed ad hoc, which may require different levels of detail depending on the problem addressed and how realistic the evaluation needs to be. Moreover, to demonstrate they are a significant contribution to the field, these new algorithms must be benchmarked against the best-performing previously proposed solutions. Due to the large set of parameters and their wide range of possible values, benchmarking algorithms from the literature is not straightforward and can quickly become challenging and time-consuming. This work introduces the Optical Networking Gym, an open-source toolkit that simplifies implementing optical resource assignment simulations and benchmarking new solutions against previously published algorithms. The toolkit provides environments modeling relevant optical networking scenarios, common algorithms for solving problems related to these scenarios, and a set of scripts to prepare and execute simulations for various use cases. Currently, four environments are available, with the possibility of increasing this number through contributions from the co-authors and the community. This paper describes the architecture, interface, environments, and scripts included with the toolkit. We adopt the quality of transmission (QoT)-aware dynamic resource allocation of optical services as the network scenario under examination. Three use cases highlight the toolkit’s modularity, flexibility, and performance. The toolkit allows researchers to streamline the process of developing simulation scenarios and algorithms, enhancing their ability to benchmark their algorithms.
光网络服务的动态供应需要算法来根据特定的服务要求和当前的网络状态找到合适的解决方案。这些算法通常使用临时开发的软件模拟器进行评估,根据所解决的问题和评估需要的现实程度,可能需要不同程度的细节。此外,为了证明这些新算法对该领域的重大贡献,必须将其与之前提出的最佳解决方案进行比较。由于参数集庞大且可能的取值范围很广,对文献中的算法进行基准测试并不简单,很快就会变得具有挑战性且耗时。这项工作介绍了 Optical Networking Gym,这是一个开源工具包,可简化光资源分配模拟的实施,并根据以前发布的算法对新解决方案进行基准测试。该工具包提供了模拟相关光网络场景的环境、解决这些场景相关问题的通用算法,以及一套用于准备和执行各种用例模拟的脚本。目前有四个环境可用,并有可能通过共同作者和社区的贡献增加环境数量。本文介绍了该工具包的架构、界面、环境和脚本。我们采用光服务的传输质量(QoT)感知动态资源分配作为研究的网络场景。三个使用案例突出了工具包的模块性、灵活性和性能。该工具包允许研究人员简化开发仿真场景和算法的过程,提高他们对算法进行基准测试的能力。
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引用次数: 0
Cognitive learning enabled agile optical network 认知学习支持敏捷光网络
IF 4 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-10-30 DOI: 10.1364/JOCN.538632
Yijun Cheng;Zejun Chen;Zihe Hu;Meng Xiang;Zhijun Yan;Yuwen Qin;Songnian Fu
Nonlinear equalization (NLE) is essential for guaranteeing the performance of an optical network (ON). Effective NLE implementation relies on key parameters of the transmission link, including the modulation format (MF) and the launch power. As ONs become more agile, the parameters of fiber optical transmission need to be adaptive and relevant to the routing condition. Therefore, successful NLE implementation relies on the realization of transmission awareness (TA). Although machine learning-enabled optical performance monitoring (OPM) has been extensively investigated in the past few years, current NLE algorithms cannot autonomously perceive transmission parameters. Furthermore, current TA implementation still needs human intervention to guide the NLE. In addition, existing ML-based OPM and NLE cannot be trained autonomously, leading to the incapability of environmental change and mislabeling. Here, we propose cognitive learning (CL) for TA-guided NLE in agile ONs. We perform an experiment involving 32 Gbaud polarization-division-multiplexed (PDM)-quadrature phase shift keying (QPSK)/16-quadrature amplitude modulation (QAM) transmission over 1500 km of standard single-mode fiber (SSMF) with a variable launch power from 0 to 3 dBm. When a deep neural network (DNN) with amplitude histograms (AHs) as inputs and one step per span-learned digital back-propagation (1stps-LDBP) are developed, the CL simultaneously enables both TA and NLE, with the capability of self-learning, mislabeling resistance, and dynamic adaptation. The proof-of-concept experimental results indicate that both the accuracy of TA and the Q-factor of PDM-16QAM can be improved by 34.8% and 0.84 dB, respectively, when the launch power is 3 dBm. Moreover, the accuracy of TA is enhanced by 35.3%, even when the used data has 30% mislabeling. Therefore, the CL framework can be customized to satisfy various NLE implementations, thereby supporting the adaptive transmission of agile ONs.
非线性均衡(NLE)对于保证光网络(ON)的性能至关重要。非线性均衡的有效实施依赖于传输链路的关键参数,包括调制格式(MF)和发射功率。随着光网络变得越来越灵活,光纤传输的参数需要自适应并与路由条件相关。因此,成功实施 NLE 有赖于实现传输感知 (TA)。尽管在过去几年中对机器学习支持的光性能监控(OPM)进行了广泛研究,但目前的 NLE 算法无法自主感知传输参数。此外,目前的 TA 实现仍然需要人工干预来指导 NLE。此外,现有的基于 ML 的 OPM 和 NLE 无法进行自主训练,导致无法应对环境变化和错误标记。在此,我们提出了认知学习(CL),用于在敏捷网络中由 TA 引导的 NLE。我们进行了一项实验,在 1500 千米标准单模光纤(SSMF)上进行 32 Gbaud 偏振分复用(PDM)-正交相移键控(QPSK)/16 正交振幅调制(QAM)传输,发射功率从 0 到 3 dBm 不等。在开发了以振幅直方图(AHs)为输入的深度神经网络(DNN)和每跨一步学习数字反向传播(1stps-LDBP)后,CL 可同时实现 TA 和 NLE,并具有自学习、抗误标记和动态适应能力。概念验证实验结果表明,当发射功率为 3 dBm 时,TA 的精度和 PDM-16QAM 的 Q 因子分别提高了 34.8% 和 0.84 dB。此外,即使所使用的数据存在 30% 的错误标记,TA 的准确度也能提高 35.3%。因此,CL 框架可以定制,以满足各种 NLE 实现,从而支持敏捷 ON 的自适应传输。
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引用次数: 0
Lifelong QoT prediction: an adaptation to real-world optical networks 终生 QoT 预测:适应真实世界的光网络
IF 4 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-10-29 DOI: 10.1364/JOCN.531851
Qihang Wang;Zhuojun Cai;Faisal Nadeem Khan
Predicting the quality of transmission (QoT) is a critical task in the management and optimization of modern fiber-optic networks. Traditional machine learning (ML) QoT prediction models, typically trained on pre-collected datasets, are designed to make long-term predictions once deployed. However, this static training strategy often falls short in the face of time-dependent network evolution and variations. We identify the root cause of these shortcomings as shifts in data distribution, which are not accounted for in conventional static models. In response to these challenges, we propose an online continual learning pipeline that is specifically designed for stable QoT prediction in optical networks. This pipeline directly addresses the problem of distribution shifts by continuously updating the prediction model in response to real-time network data. We explore and compare various strategies within this framework and demonstrate that the integration of the adaptive retraining strategy and the regularized online continual learning algorithm (OCL-REG) significantly enhances the QoT prediction stability while optimizing the resource efficiency. OCL-REG demonstrates superior adaptability and stability, achieving an average cumulative mean squared error (C-MSE) of 0.19 on a testbench with a data distribution shift sequence containing 1000 batches. Moreover, the OCL-REG model requires fewer samples for adaptation, averaging around 107 samples, compared to the conventional retraining strategy, which requires an average of 253 samples. Our approach presents a paradigm shift in QoT prediction, moving from a static to a dynamic, lifelong learning model that is more attuned to the evolving realities of real fiber-optic networks.
预测传输质量(QoT)是管理和优化现代光纤网络的一项关键任务。传统的机器学习(ML)QoT 预测模型通常在预先收集的数据集上进行训练,旨在部署后进行长期预测。然而,面对随时间变化的网络演进和变化,这种静态训练策略往往会出现不足。我们发现这些缺陷的根本原因在于数据分布的变化,而传统的静态模型并没有考虑到这一点。为了应对这些挑战,我们提出了一种在线持续学习管道,专门用于光网络中稳定的 QoT 预测。该管道根据实时网络数据不断更新预测模型,直接解决了分布偏移的问题。我们探索并比较了这一框架中的各种策略,结果表明,自适应再训练策略与正则化在线持续学习算法(OCL-REG)的整合能显著提高 QoT 预测的稳定性,同时优化资源效率。OCL-REG 展示了卓越的适应性和稳定性,在包含 1000 个批次的数据分布转移序列的测试平台上实现了 0.19 的平均累积均方误差 (C-MSE)。此外,与平均需要 253 个样本的传统再训练策略相比,OCL-REG 模型所需的适应样本更少,平均约为 107 个样本。我们的方法实现了 QoT 预测的范式转变,从静态模型转变为动态的终身学习模型,更加适应实际光纤网络不断发展的现实。
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引用次数: 0
Segmented protection scheme based on maximum bandwidth sharing in F5G 基于 F5G 最大带宽共享的分段保护方案
IF 4 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-10-28 DOI: 10.1364/JOCN.529958
Wenhong Liu;Yongli Zhao;Yajie Li;Xin Li;Sabidur Rahman;Jie Zhang
As guaranteed reliable experience (GRE) is one of the features of fifth-generation fixed networks (F5G), high-reliability optical transport networks (OTNs) have become one of the key technologies supporting this feature. Unfortunately, current OTN protection methods often provide fixed bandwidth for protection of 1 Gbps or more, which leads to resource wastage. Fine grain OTN (fgOTN) is an extension of existing OTN, which supports hitless bandwidth adjustment and uses 10 Mbps time slot isolation. The application of fgOTN’s advantages to network protection can save resources. However, how much initial protection bandwidth is reserved for links to improve the service recovery success probability after faults is a key issue to be studied. If the initially reserved protection bandwidth is too much, that may waste precious bandwidth resources and fail to recover other services. If the initially reserved protection bandwidth is too small, the controller needs to adjust the bandwidth frequently to meet service requirements, which puts tremendous pressure on network management and control. This study proposes a maximum bandwidth segmented shared protection (MBSSP) scheme, which is based on optimized centralized and distributed collaboration network management architecture. The protection scheme includes two algorithms: (i) the resource reservation algorithm used before the fault occurs based on maximum bandwidth segmented shared protection and (ii) the protection switch algorithm used after the fault occurs based on bandwidth adjustment. Simulative results show that, in a 38-node topology, compared with minimum bandwidth dedicated protection (MBDP), MBSSP only sacrifices 0.8% of resource utilization but can reduce the bandwidth adjustment probability by 15.8% and improves the recovery success probability by 33.4%. Compared with end-to-end shared protection (E2ESP), MBSSP improves recovery success probability by 42.9% and saves resources by 16.7%, although it increases the bandwidth adjustment probability by 20%.
保证可靠体验(GRE)是第五代固定网络(F5G)的特性之一,因此高可靠性光传输网络(OTN)已成为支持这一特性的关键技术之一。遗憾的是,目前的 OTN 保护方法通常提供 1 Gbps 或更高的固定保护带宽,从而导致资源浪费。细粒度 OTN(fgOTN)是现有 OTN 的扩展,它支持无命中带宽调整,并使用 10 Mbps 时隙隔离。将 fgOTN 的优势应用于网络保护可以节省资源。然而,为链路预留多少初始保护带宽才能提高故障后服务恢复的成功率是一个需要研究的关键问题。如果初始预留的保护带宽过多,可能会浪费宝贵的带宽资源,并且无法恢复其他服务。如果初始预留的保护带宽过小,控制器就需要频繁调整带宽以满足业务需求,这给网络管理和控制带来了巨大压力。本研究提出了一种最大带宽分段共享保护(MBSSP)方案,该方案基于优化的集中式和分布式协作网络管理架构。该保护方案包括两种算法:(i) 故障发生前使用的基于最大带宽分段共享保护的资源预留算法;(ii) 故障发生后使用的基于带宽调整的保护切换算法。仿真结果表明,在 38 节点拓扑中,与最小带宽专用保护(MBDP)相比,MBSSP 仅牺牲了 0.8% 的资源利用率,却能将带宽调整概率降低 15.8%,将恢复成功概率提高 33.4%。与端到端共享保护(E2ESP)相比,MBSSP 提高了 42.9% 的恢复成功率,节省了 16.7% 的资源,但增加了 20% 的带宽调整概率。
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引用次数: 0
Raman amplifier design and launch power optimization in multi-band optical systems 多波段光学系统中的拉曼放大器设计和发射功率优化
IF 4 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2024-10-25 DOI: 10.1364/JOCN.534006
Andre Souza;Nelson Costa;Joao Pedro;Joao Pires
We propose an innovative optimization framework using a multi-objective genetic algorithm to simultaneously optimize the launch power profile and design Raman amplifiers. Its flexibility allows us to find better solutions and reduce the number of Raman pumps. Moreover, we utilize the framework to compare the potential of four multi-band transmission systems leveraging hybrid fiber amplification. Simulation results highlight that complementing a C + L-band system with the S-band leads to higher total system capacity than using the E-band or interleaving data channels and Raman pumps.
我们提出了一种创新的优化框架,利用多目标遗传算法同时优化发射功率曲线和设计拉曼放大器。它的灵活性使我们能够找到更好的解决方案,并减少拉曼泵的数量。此外,我们还利用该框架比较了四种利用混合光纤放大的多波段传输系统的潜力。仿真结果表明,与使用 E 波段或交错数据通道和拉曼泵相比,使用 S 波段对 C + L 波段系统进行补充可提高系统总容量。
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引用次数: 0
期刊
Journal of Optical Communications and Networking
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