Autonomous maintenance for satellite-terrestrial integrated networks

星地一体化网络自主维护

• 批准号: RGPIN-2022-03364
• 负责人: Hu, Peng
• 金额: $ 1.89万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=765764
• 关键词: Autonomous; maintenance; satellite; terrestrial; integrated

Reliable broadband Internet has never become so indispensable in our daily lives during and after the pandemic world. However, in 2021 alone, days of countrywide Internet outages have happened a few times. The Rogers network outage in April and social media service outage in October caused billion-dollar costs. The future Internet will face serious challenges. On the one hand, it is expected to provide global broadband access to more than 85% of the global population who currently have no broadband as reported by the International Telecommunications Union. On the other hand, highly resilient Internet access needs to be ensured with the increasing complexity of global telecommunications infrastructures in space and ground segments. With the new launch plans for massive non-geostationary (NGSO) satellites, the future Internet infrastructure will brace the convergence of satellite and terrestrial networks based on a new paradigm called satellite-terrestrial integrated network (STIN). A STIN is envisioned to enable global broadband Internet with the integration of advanced medium-Earth-orbit (MEO) and low-Earth-orbit (LEO) satellite constellations into heterogeneous ground segments. However, this vision can hardly be fulfilled without effective maintenance and operations for resilience assurance. For example, malfunctioning components, atmospheric events, or anomalous traffic on any network segment can easily degrade or disrupt network services. The complex, heterogeneous, and dynamic nature of the space and ground components introduces persistent operations challenges. Equipping STINs with an autonomous maintenance (AM) capability offers an ideal solution to the challenges. Such a solution can handle the increasing complexity of STINs and mitigate performance degradation. The long-term goal of the proposed research is to develop novel AM approaches to making the STIN-based Internet infrastructure resilient, intelligent, and self-maintainable. The short-term objectives are to explore the fundamental elements of AM in root cause analysis and anomaly mitigation for an NGSO-satellite-based STIN infrastructure. The proposed research will be conducted through holistic data-driven STIN architectures, generalizable anomaly detection models, and anomaly mitigation schemes with novel machine learning (ML) models and frameworks. The proposed research will advance the field by creating approaches and techniques that can be applied to autonomous management for any STIN-related network. The research will generate impact in academia and industry and ultimately boost the digital economy worldwide. It will also contribute to Canada's national priority for enhancing the digital infrastructure for unserved and underserved areas. HQP will be trained to conduct key research objectives and gain unique and transferrable skills sets of ML, data analytics, networking, and software development, making them highly competitive in securing positions in academia and industry.

在大流行世界期间和之后，可靠的宽带互联网在我们的日常生活中从未如此必不可少。但是，仅在2021年，几天的互联网停电发生了几次。 Rogers Network在四月的停电，10月的社交媒体服务中断造成了十亿美元的成本。未来的互联网将面临严峻的挑战。一方面，预计将为全球超过85％的全球人口提供全球宽带访问，这些全球人口目前没有宽带，如国际电信联盟所报告的那样。另一方面，随着空间和地面细分市场中全球电信基础设施的复杂性的增加，需要确保高度弹性的互联网访问。借助大规模非震荡（NGSO）卫星的新发布计划，未来的互联网基础架构将基于一种称为卫星 - 物流综合网络（STIN）的新范式来支撑卫星和地面网络的收敛性。设想，通过将高级中等轨道（MEO）和低轨道（LEO）卫星星座集成到异质地面段中，可以使全球宽带Internet实现全球宽带互联网。但是，如果没有有效的维护和弹性保证，几乎无法实现这种愿景。例如，在任何网络细分市场上，组件，大气事件或异常流量都可以轻松降低或破坏网络服务。空间和地面组件的复杂，异构和动态性质引入了持续的操作挑战。 为STIN提供自主维护（AM）功能，为挑战提供了理想的解决方案。这样的解决方案可以处理Stins增加的复杂性并减轻性能降解。拟议研究的长期目标是开发新颖的AM方法，以使基于STIN的Internet基础设施具有韧性，聪明和自我维护。短期目标是探讨基于NGSO-卫星基础设施的根本原因分析和缓解异常的基本要素。拟议的研究将通过整体数据驱动的STIN架构，可概括的异常检测模型以及具有新型机器学习（ML）模型和框架的缓解异常方案进行。拟议的研究将通过创建可以应用于任何与STIN相关网络的自动管理的方法和技术来推进该领域。这项研究将对学术界和行业产生影响，并最终在全球范围内提高数字经济。它还将为加拿大的国家优先事项做出贡献，以增强未服务和服务不足的地区的数字基础设施。 HQP将经过培训，以实现关键的研究目标，并获得ML，数据分析，网络和软件开发的独特而可转让的技能集，从而使它们在确保学术界和行业的职位方面具有很高的竞争力。