In satellite computing applications, such as remote sensing, tasks often involve similar or identical input data, leading to the same processing results. Computation reuse is an emerging paradigm that leverages the execution results of previous tasks to enhance the utilization of computational resources. While this paradigm has been extensively studied in terrestrial networks with abundant computing and caching resources, such as named data networking (NDN), it is essential to develop a framework appropriate for resource-constrained satellite networks, which are expected to have longer task completion times. In this paper, we propose CCRSat, a collaborative computation reuse framework for satellite edge computing networks. CCRSat initially implements local computation reuse on an independent satellite, utilizing a satellite reuse state (SRS) to assess the efficiency of computation reuse. Additionally, an inter-satellite computation reuse algorithm is introduced, which utilizes the collaborative sharing of similarity in previously processed data among multiple satellites. The evaluation results tested on real-world datasets demonstrate that, compared to comparative scenarios, our proposed CCRSat can significantly reduce task completion time by up to 62.1% and computational resource consumption by up to 28.8%.

翻译：在卫星计算应用中，例如遥感领域，任务通常涉及相似或相同的输入数据，从而导致相同的处理结果。计算复用是一种新兴范式，它利用先前任务的执行结果来提升计算资源的利用率。尽管该范式已在具有丰富计算和缓存资源的地面网络（如命名数据网络NDN）中得到广泛研究，但为资源受限的卫星网络开发一个合适的框架至关重要，这类网络通常预期具有更长的任务完成时间。本文提出CCRSat，一种面向卫星边缘计算网络的协同计算复用框架。CCRSat首先在独立卫星上实现本地计算复用，利用卫星复用状态（SRS）来评估计算复用的效率。此外，还引入了一种星间计算复用算法，该算法利用多颗卫星之间先前处理数据相似性的协同共享。在真实数据集上的测试评估结果表明，与对比场景相比，我们提出的CCRSat能够将任务完成时间最多降低62.1%，并将计算资源消耗最多减少28.8%。