Renewables Power the Orbit? Achieving Sustainable Space Edge Computing via QoS-Aware Offloading
Xiaoyi Fan (1), Yi Ching Chou (2), Hao Fang (2), Long Chen (2), Haoyuan Zhao (2), Ershun Du (1), Chongqing Kang (1), Zhe Chen (3), Jiangchuan Liu (2) ((1) Department of Electrical Engineering, Tsinghua University, China, (2) School of Computing Science, Simon Fraser University

TL;DR
This paper introduces SQSO, a framework for sustainable, QoS-aware task offloading from LEO satellites to renewable-powered data centers, significantly reducing energy use and battery wear while maintaining performance.
Contribution
It presents a novel co-design approach and an adaptive offloading algorithm that jointly optimize satellite data offloading considering dynamic communication and energy constraints.
Findings
AO^2 reduces energy consumption by up to 76.03%.
AO^2 cuts battery life consumption by up to 76.85%.
AO^2 lowers task delay compared to existing schemes.
Abstract
Low-Earth-Orbit (LEO) satellite constellations are becoming integral to 6G infrastructure, but increasing in-orbit computation accelerates battery degradation and raises sustainability concerns. Meanwhile, renewable-heavy regions worldwide experience persistent energy curtailment due to transmission bottlenecks, leaving substantial clean energy stranded near generation sites. We identify a satellite-grid co-design opportunity: adaptively offloading task-critical data from satellite to data centers co-located with renewable power plants. However, realizing this vision requires jointly considering intermittent and capacity-limited communication windows, as well as time-varying electricity budgets. In this paper, we propose SQSO, a Sustainable and QoS-aware Satellite Offloading framework that models per-interval task offloading as a constrained optimization over dynamic topology and…
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