Haoyuan Zhao

Long Chen, Hao Fang, Yi Ching Chou et al.

Low Earth Orbit (LEO) satellite networks such as Starlink and Project Kuiper are increasingly integrated with cloud infrastructures, forming an important internet backbone for global web services. By extending connectivity to remote regions, oceans, and disaster zones, these networks enable reliable access to applications ranging from real-time WebRTC communication to emergency response portals. Yet the resilience of these web services is threatened by space radiation: it degrades hardware, drains batteries, and disrupts continuity, even if the space-cloud integrated providers use machine learning to analyze space weather and radiation data. Specifically, conventional fixes like altitude adjustments and thermal annealing consume energy; neglecting this energy use results in deep discharge and faster battery aging, whereas sleep modes risk abrupt web session interruptions. Efficient network-layer mitigation remains a critical gap. We propose RALT (Radiation-Aware LEO Transmission), a control-plane solution that dynamically reroutes traffic during radiation events, accounting for energy constraints to minimize battery degradation and sustain service performance. Our work shows that unlocking space-based web services' full potential for global reliable connectivity requires rethinking resilience through the lens of the space environment itself.

Xiaoyi Fan, Yi Ching Chou, Hao Fang et al.

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 electricity prices. Under this framework, we design $\text{AO}^2$, an adaptive offloading orchestration algorithm to solve the formulated optimization problem. Using Starlink-scale simulations and real-world electricity price traces, $\text{AO}^2$ reduces energy consumption by up to 76.03% and battery life consumption by up to 76.85% compared to state-of-the-art schemes, while also lowering task delay. This work highlights that sustainable scaling of LEO constellations requires co-design of space networking and renewable energy infrastructure, while our solution promotes renewable-aware task offloading and cross-domain collaboration for space-energy integration in the 6G era.

Haoyuan Zhao, Long Chen, Yi Ching Chou et al.

The emerging demand for Earth observation (EO) to address environmental challenges has driven unprecedented growth in its primary carrier, Low Earth Orbit satellites, in recent years. Ground stations (GSs), the egress points of these networks, are congested due to the massive volume of EO traffic, and their deployment is constrained by geographic, political, and budgetary factors. Although inter-satellite links (ISLs) can partially relieve this congestion by forwarding traffic to alternative GSs, existing ISL-based approaches can hardly address traffic contention caused by biased GS distribution and may also raise sustainability concerns due to prolonged ISL paths. In this paper, we propose OrbitTransit, a pickup-carry-offload (PCO) approach that leverages satellite mobility for data \textit{delivery} and integrates ISLs for traffic \textit{diffusion} to alleviate the resource contention inherent in PCO delivery. The proposed orbit-as-node framework and contention-avoidant delivery jointly determine the optimal hybrid PCO-ISL path, minimizing energy consumption and balancing GS traffic. Extensive experiments show that OrbitTransit reduces battery consumption by $47.16\%$, decreases task failures by $1.09\times$, and improves GS load balancing compared with state-of-the-art GS selection and routing algorithms.