Juan A. Fraire

Researcher in Space Networking and Informatics

Inria CONICET Saarland University

Publications Preprint · Orbital computing · 2026

Ungrounded Computing in Low-Earth Orbit: A Sustainability Audit

Juan A. Fraire, Robin Ohs, Gregory F. Stock, Andreas Schmidt, and Holger Hermanns

HAL preprint, 2026

Read on HALfree

ShareLinkedInXBlueskyEmail

Abstract

Orbital data centers are marketed as the sustainable answer to the energy, water, and land that terrestrial AI consumes. Constellations of computing satellites have been filed and demonstrators already fly, yet none of the filings we reviewed reports a lifecycle carbon assessment. This article runs the numbers the pitch leaves out. Using our lifecycle models, we audit the promises in three acts: the carbon of getting there (with launch and re-entry, orbital electricity is 1.5 to 2 times as carbon-intensive as terrestrial solar), the mass of staying alive (the radiator outweighs the GPU it cools three to twelve times over), and the price of never repairing (guaranteeing a sealed node’s survival adds 77–86% to its lifecycle carbon). Sustainability turns out to be a region of the design space, possibly an empty one, and we outline the research agenda needed to map it before these ungrounded ambitions leave the ground.

Cite

BibTeX
@article{fraire2026ungrounded,
  author  = {Fraire, Juan A. and Ohs, Robin and Stock, Gregory F. and Schmidt, Andreas and Hermanns, Holger},
  title   = {Ungrounded Computing in Low-Earth Orbit: A Sustainability Audit},
  journal = {HAL preprint},
  year    = {2026},
  url     = {https://hal.science/hal-05849193}
}

More on orbital computing

  1. Dark Clouds Rising in Low-Earth Orbit: On Environmental Limits to Massive Orbital AI Robin Ohs, Gregory F. Stock, Andreas Schmidt, Juan A. Fraire, Jörg Ott, and Holger Hermanns ACM Workshop on LEO Networking and Communication (LEO-NET), co-located with ACM SIGCOMM, 2026
    Abstract

    In 2026, we saw rising numbers of proposals for orbital data centers to facilitate AI, e.g., by SpaceX (up to one million satellites), Blue Origin, and Google—yet none include rigorous lifecycle sustainability analysis. We present ESpaS-ODC, a lifecycle carbon model that accounts for the three subsystems physically unavoidable at GPU-class power densities but absent from prior work: a thermal radiator sized from ISS data, solar-array degradation and eclipse margin, and cold-standby spares for no-repair access. Applying the model to an edge data center in a 510 km orbit reveals that the service-overhead-scaled radiator weighs about eleven times the GPU it serves and that modeled power and thermal infrastructure dominate launched component mass—not compute. Using mission duration T as the denominator to amortize launch, re-entry, and manufacturing carbon, model-boundary parity with a global-average terrestrial DC occurs within the first two mission years in our parameter sweep. With respect to a renewables-powered green-energy DC (Finland grid intensity: 68 gCO2e/kWh, PUE: 1.2), parity requires multi-year missions with cold-standby spares compensating the shorter component lifetimes. Idealized dawn-dusk SSO (no-eclipse regime, β > βcrit) eliminates the eclipse battery, cutting modeled component mass significantly (e.g., 25% on the 1 kW-ODC for a 3 yr mission), but leaves the radiator unchanged: high-beta orbits solve the battery problem, not the thermal problem. Finally, carrying one full cold spare (r = 2) increases amortized carbon per GPU hour by 40% on Starship and 34% on Falcon-9 at T = 3 yr, while its dependability benefit remains to be quantified.

  2. Optimal Design of Space-Based Data Center Constellations for In-Orbit Computing Services Wenxiao Ge, Juan A. Fraire, and Kanglian Zhao IEEE Communications Letters, 2026
    Abstract

    With the increasing demand for in-orbit computing services, the architectural design of Space-Based Data Center (SBDC) constellations has emerged as a critical research challenge. However, existing design methodologies remain tailored to traditional constellations and lack specialized models to evaluate the unique cost-performance trade-offs. This letter proposes a comprehensive multi-objective optimization model for SBDC constellation design, aiming to minimize cost and delay while maximizing computational performance. To efficiently solve this complex problem, a novel SBDC Constellation Design Optimization (SCDO) framework, built upon NSGA-II, is developed to obtain the optimal constellation architectures. Extensive simulations demonstrate the effectiveness of the proposed framework, reveal two primary design paradigms, and provide an in-depth analysis of the impact of task characteristics.

  3. Space Cloud Networks: Technologies, Architectures, and Key Enablers Wenxiao Ge, Juan A. Fraire, Xinxin Shen, and Kanglian Zhao IEEE Communications Magazine, 2026
    Abstract

    The rapid growth of artificial intelligence models and global computing demands has placed an unsustainable burden on ground-based data centers, exacerbating energy consumption and environmental concerns. Simultaneously, emerging space-based infrastructures face stringent real-time processing requirements, while underserved regions experience persistent connectivity gaps. To address these challenges, we propose a space cloud network powered by space-based data centers interconnected through high-speed laser links. We present a three-layer architecture comprising cloud, access, and user layers and analyze the strengths and limitations of different orbits and configurations. We advocate for a multi-layer heterogeneous fusion network that leverages dawn-dusk and inclined orbits to balance performance, latency, and coverage. Additionally, we identify key enabling technologies, including space cloud operating systems, file systems, network management, and network security. This work presents a comprehensive framework for establishing the space cloud network, aiming to enhance global connectivity and computational efficiency.