This paper addresses the challenge of efficiently offloading heavy computing tasks from ground mobile devices to the satellite-based mist computing environment. With ground-based edge and cloud servers often being inaccessible, the exploitation of satellite mist computing becomes imperative. Existing offloading algorithms have shown limitations in adapting to the unique characteristics of heavy computing tasks. Thus, we propose a heavy computing task offloading algorithm that prioritizes satellite proximity. This approach not only reduces energy consumption during telecommunications but also ensures tasks are executed within the specified timing constraints, which are typically non-time-critical. Our proposed algorithm outperforms other offloading schemes in terms of satellites energy consumption, average end-to-end delay, and tasks success rates. Although it exhibits a higher average VM CPU usage, this increase does not pose critical challenges. This distance-based approach offers a promising solution to enhance energy efficiency in satellite-based mist computing, making it well-suited for heavy computing tasks demands.

翻译：本文针对地面移动设备向卫星雾计算环境高效卸载重型计算任务的挑战展开研究。由于地面边缘服务器和云服务器常无法接入，利用卫星雾计算势在必行。现有卸载算法在适应重型计算任务独特特性方面存在局限性。为此，我们提出一种优先考虑卫星邻近度的重型计算任务卸载算法。该方法不仅降低了通信过程中的能耗，还能确保任务在指定的时间约束内完成执行（这些约束通常为非实时性要求）。与其它卸载方案相比，本算法在卫星能耗、平均端到端时延及任务成功率方面均具优势。尽管该算法的平均虚拟机CPU使用率较高，但并未带来关键性挑战。这种基于距离的算法为提升卫星雾计算能效提供了有效解决方案，特别适合满足重型计算任务的需求。