Juan A. Fraire

Researcher in Space Networking and Informatics

Inria CONICET Saarland University

Publications Conference paper · Orbital computing · 2026

MeteorNet: Continuous-Time Emulation Platform for Edge Intelligence in LEO Constellations

Juan A. Fraire, Camilo Rojas Milla, Fabio Patrone, and Mario Marchese

IEEE International Mediterranean Conference on Communications and Networking (MeditCom), pp. 1–6, 2026

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Abstract

Mega-constellations of Low Earth Orbit (LEO) satellites are enabling a new Space Cloud paradigm in which edge servers hosted on-board process tasks autonomously, reducing ground-segment latency for globally dispersed users. Realizing this vision requires Collaborative Edge Intelligence (CEI): distributed algorithms that coordinate Multi-access Edge Computing (MEC) server activation, task offloading, and routing across a time-varying orbital topology. Existing evaluation tools are inadequate—simulation platforms abstract away protocollevel behavior, while emulation testbeds lack orbital dynamics. This paper presents MeteorNet, an open-source, continuous-time emulation platform that integrates SGP4 orbital propagation, Mininet/ONOS network emulation, Docker-containerized MEC services, and MongoDB telemetry. Supporting eight orchestration strategies, including Fuzzy Logic and distributed Reinforcement Learning controllers, MeteorNet enables apples-to-apples CEI benchmarking under realistic orbital conditions. Experiments show that intelligent controllers halve the MEC activation cost at low load, while revealing an orbital-visibility bottleneck that limits task success at high load, regardless of the orchestration policy.

Cite

DOI 10.1109/meditcom67211.2026.11641012

BibTeX
@inproceedings{fraire2026meteornet,
  author    = {Fraire, Juan A. and Rojas Milla, Camilo and Patrone, Fabio and Marchese, Mario},
  title     = {{MeteorNet}: Continuous-Time Emulation Platform for Edge Intelligence in {LEO} Constellations},
  booktitle = {IEEE International Mediterranean Conference on Communications and Networking (MeditCom)},
  pages     = {1--6},
  year      = {2026},
  doi       = {10.1109/meditcom67211.2026.11641012}
}

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.