标题： 天空之上的空间：将全球规模的地面站作为服务以实现高效的轨道数据处理 显示英文标题

标题： The Space above the Sky: Uniting Global-Scale Ground Station as a Service for Efficient Orbital Data Processing

摘要： 大型地球观测低地轨道卫星星座每天收集大量的图像数据。 这些数据量需要通过地面站传输到数据中心进行处理。 地面站即服务（GSaaS）作为一种新的云服务，为卫星运营商提供按使用付费的地面站网络访问服务。 然而，租用地面站和数据中心资源仍然会带来相当大的成本，尤其是对于大规模的卫星星座。 目前坚持使用单一GSaaS供应商的做法，由于地面站可用性有限，也存在高数据延迟和对天气变化适应性差的问题。 为了解决这些限制，我们提出了SkyGS，一种通过在多个云提供商之间联合GSaaS和云计算服务来调度通信和计算的系统。 我们将 resulting 问题建模为一个具有长期数据延迟阈值约束的系统成本最小化问题。 在SkyGS中，我们应用Lyapunov优化将长期优化问题分解为一系列不需要先验知识的实时优化问题。 由于分解后的问题仍然具有指数复杂度，我们将其转换为二分图匹配问题，并采用匈牙利算法来解决它。 我们从理论上分析了性能，并使用基于真实世界卫星、地面站和数据中心数据的现实模拟评估了SkyGS。 全面的实验表明，SkyGS可以实现高达63%的成本节约，并将平均数据延迟降低高达95%。 显示英文摘要

摘要： Large constellations of Earth Observation Low Earth Orbit satellites collect enormous amounts of image data every day. This amount of data needs to be transferred to data centers for processing via ground stations. Ground Station as a Service (GSaaS) emerges as a new cloud service to offer satellite operators easy access to a network of ground stations on a pay-per-use basis. However, renting ground station and data center resources still incurs considerable costs, especially for large satellite constellations. The current practice of sticking to a single GSaaS provider also suffers high data latency and low robustness to weather variability due to limited ground station availability. To address these limitations, we propose SkyGS, a system that schedules both communication and computation by federating GSaaS and cloud computing services across multiple cloud providers. We formulate the resulting problem as a system cost minimization problem with a long-term data latency threshold constraint. In SkyGS, we apply Lyapunov optimization to decompose the long-term optimization problem into a series of real-time optimization problems that do not require prior knowledge. As the decomposed problem is still of exponential complexity, we transform it into a bipartite graph-matching problem and employ the Hungarian algorithm to solve it. We analyze the performance theoretically and evaluate SkyGS using realistic simulations based on real-world satellites, ground stations, and data centers data. The comprehensive experiments demonstrate that SkyGS can achieve cost savings by up to 63% & reduce average data latency by up to 95%.