协同轨道边缘智能：一种面向空间高效能计算的去中心化范式
Collaborative Orbital Edge Intelligence: A Decentralized Paradigm for Energy-Efficient Computing in Space
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中文总结 AI 辅助
针对现有轨道边缘计算集中式控制的缺陷，本文提出协同轨道边缘智能（COEI）范式，通过LEO卫星去中心化协作实现空间数据高效能在轨处理，并通过任务卸载案例验证其优势。
中文摘要 AI 辅助
近年来，低地球轨道（LEO）卫星部署日益增多，以实现偏远及灾害多发地区的连通性。研究人员提出了轨道边缘计算，该技术为LEO卫星增添计算智能，在轨处理数据，提供贴近空间数据源的边缘智能。现有轨道边缘计算研究通常采用集中式控制，未考虑不同运营商卫星间的协作，导致连通性受限、延迟更高、卫星电池消耗增加，且未充分探究异构LEO星座下实现高效能智能的去中心化星间协作。本文提出一种新型范式——协同轨道边缘智能（COEI），其利用LEO卫星间的去中心化协作，实现空间数据的高效能在轨处理。我们描述了COEI的整体系统架构，包括与网络、计算及电源管理相关的问题。COEI可助力构建多方多轨道卫星巨型星座，通过提供全球弹性连通性、实时智能及高效能服务等优势，提升服务质量。为验证COEI的优势，我们针对去中心化感知能量的卫星任务卸载开展案例研究，目标是最大化任务成功率，同时最小化所有卫星的最大放电深度之和。最后，我们概述了COEI的未来研究方向，为进一步探索提供机遇。
英文摘要
In recent years, Low Earth Orbit (LEO) satellites have been increasingly deployed to enable connectivity in remote and disaster-prone areas. Researchers have proposed Orbital Edge Computing, which adds computational intelligence to LEO satellites to process data on orbit, providing edge intelligence close to space data sources. Existing work on Orbital Edge Computing typically assumes centralized control without collaboration among satellites from different providers, leading to limited connectivity, higher latency, and increased satellite battery depletion. They have not fully explored decentralized inter-satellite collaboration for energy-efficient intelligence under heterogeneous LEO constellations. This paper introduces a novel paradigm, Collaborative Orbital Edge Intelligence (COEI), that leverages decentralized collaboration among LEO satellites to enable energy-efficient on-orbit processing of space data. We describe the overall system architecture of COEI, including the issues related to networking, computing, and power management. COEI can help create a multi-party, multi-orbit megaconstellation of satellites that delivers better service quality by providing benefits, including global resilient connectivity, real-time intelligence, and energy-efficient services. To demonstrate the COEI benefits, we conduct a case study on decentralized energy-aware satellite task offloading to maximize the task success rate while minimizing the sum of the maximum battery depth-of-discharge across all satellites. Finally, we outline future directions for COEI that offer opportunities for further investigation.
