论文标题
审查光网络中基于机器学习的故障管理
A Review of Machine Learning-based Failure Management in Optical Networks
论文作者
论文摘要
故障管理在光网络中起着重要作用。它确保安全操作，减轻潜在风险并执行主动保护。机器学习（ML）被认为是进行全面数据分析和复杂网络管理的一种非常强大的技术，并且被广泛用于光网络中的故障管理以彻底改变传统的手动方法。在这项研究中，详细说明了典型的失败任务，物理对象，ML算法，数据源和提取的信息，引入了故障管理的背景。根据警报分析，故障预测，故障检测，失败定位和故障识别，提供了ML在故障管理中的应用概述。最后，从数据，模型，任务和新兴技术的角度讨论了ML的未来指示进行故障管理。
Failure management plays a significant role in optical networks. It ensures secure operation, mitigates potential risks, and executes proactive protection. Machine learning (ML) is considered to be an extremely powerful technique for performing comprehensive data analysis and complex network management and is widely utilized for failure management in optical networks to revolutionize the conventional manual methods. In this study, the background of failure management is introduced, where typical failure tasks, physical objects, ML algorithms, data source, and extracted information are illustrated in detail. An overview of the applications of ML in failure management is provided in terms of alarm analysis, failure prediction, failure detection, failure localization, and failure identification. Finally, the future directions on ML for failure management are discussed from the perspective of data, model, task, and emerging techniques.
