CAREER: Networking and Compute for Next Generation Low-Earth Orbit Satellites

致力于地球观测的下一代低地球轨道(LEO)卫星寻求实现一个令人信服的愿景：对地球进行频繁的高分辨率监测，以跟踪人类规模的事件。这些卫星在离地球不到1000公里的低轨道上运行，并使获取地球图像的途径大众化，可用于多种应用：提高农业产量和收入的精准农业、早期发现森林火灾等灾害管理、疾病传播模型、地缘政治分析和气候监测。随着这样的星座扩展到数百颗卫星，传统的天地连接架构无法满足它们的需求。具体地说，这些星座每天产生数百兆兆字节的数据，必须传输到地球上，而卫星相对于地球上的地面站以快速的速度运行。因此，数据下载过程经历了一天级别的延迟，并且容易由于恶劣天气或硬件错误而失败。这一提议的目标是设计一种新的天地连接模式，消除这些瓶颈，并使容错网络能够从这些卫星收集的数据中产生近乎实时(分钟级)的洞察。拟议的研究将消除低轨卫星的网络和计算瓶颈，并使新的商业、学术和国家安全应用成为可能。一些示例应用包括对飞机入侵、森林火灾和地缘政治事件的早期反应。这项提议中的教育努力将培养学生从事以天地联网和边缘计算为重点的研究和开发工作。拟议的研究为卫星和地面站的联网和边缘计算设计新的算法和架构。具体地说，拟议的研究包括：(A)一种新的分布式地面站体系结构，它对瞬时故障具有健壮性，对业务变化灵活，并能够从卫星下载低延迟数据；(B)边缘计算框架，该框架提取洞察力，调度数据传输，并为联网传输的重要图像确定优先顺序，同时可扩展到多种应用；以及(C)设计和分析通信和地球观测卫星之间的互连，以实现机会路由。该提案对大规模天地网络采取端到端系统级别的方法，这对其健壮、容错和高性能运行至关重要。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The next generation of Low Earth Orbit (LEO) satellites, dedicated to Earth observation, seeks to enable a compelling vision: frequent high-resolution monitoring of the Earth to track humanity scale events. These satellites operate in low orbits, less than 1000 Km above Earth, and democratize access to Earth imagery for multiple applications: precision agriculture that improves farm yields and incomes, disaster management such as early detection of forest fires, modeling the spread of diseases, geo-political analytics, and climate monitoring. As such constellations scale to hundreds of satellites, traditional architectures for space-Earth connectivity fail to meet their needs. Specifically, these constellations generate hundreds of terabytes of data every day that must be transported to the Earth, while the satellites travel at fast speeds with respect to ground stations on the Earth. Therefore, the data download process experiences day-level delays and is prone to failures due to bad weather or hardware errors. The goal of this proposal is to design a new paradigm for space-Earth connectivity that removes these bottlenecks and enables fault-tolerant networks that generate near-realtime (minute-level) insights from data collected by these satellites. The proposed research will remove networking and compute bottlenecks for LEO satellites and enables novel commercial, academic, and national security applications. Some example applications include early response to aircraft intrusions, forest fires, and geopolitical events. The educational efforts in this proposal will train students to engage in research and development efforts focused on space-Earth networking and edge computing.The proposed research designs new algorithms and architectures for networking and edge computing on satellites and ground stations. Specifically, the proposed research includes: (a) a new distributed ground station architecture that is robust to transient failures, agile to traffic variations, and enables low latency data download from satellites, (b) an edge computing framework that extracts insights, schedules data transfer, and prioritizes important imagery for networked transfer while being scalable to multiple applications, and (c) design and analysis of interconnects between communication and Earth observation satellites for opportunistic routing. The proposal takes an end-to-end systems level approach to large-scale space-Earth networks, which is essential for their robust, fault-tolerant, and high-performance operation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.