The Space above the Sky: Uniting Global-Scale Ground Station as a Service for Efficient Orbital Data Processing
Heng Zhao, Sheng Cen, Yifei Zhu

TL;DR
SkyGS is a federated system that optimizes satellite data transfer and processing across multiple ground station and cloud providers, significantly reducing costs and data latency.
Contribution
It introduces a novel federated scheduling system using Lyapunov optimization and bipartite graph matching to improve efficiency and robustness in satellite data processing.
Findings
Cost savings of up to 63% achieved
Average data latency reduced by up to 95%
Effective real-time scheduling without prior knowledge
Abstract
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…
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Taxonomy
TopicsSpacecraft Design and Technology · Distributed and Parallel Computing Systems · Distributed systems and fault tolerance
