CCRSat: A Collaborative Computation Reuse Framework for Satellite Edge Computing Networks
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arXiv
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| Format: | Preprint |
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2025
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| author | Zhang, Ye Shen, Zhishu Jiang, Dawen Liu, Xiangrui Zheng, Qiushi Jin, Jiong |
| author_facet | Zhang, Ye Shen, Zhishu Jiang, Dawen Liu, Xiangrui Zheng, Qiushi Jin, Jiong |
| contents | 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%. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_11946 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | CCRSat: A Collaborative Computation Reuse Framework for Satellite Edge Computing Networks Zhang, Ye Shen, Zhishu Jiang, Dawen Liu, Xiangrui Zheng, Qiushi Jin, Jiong Distributed, Parallel, and Cluster Computing 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%. |
| title | CCRSat: A Collaborative Computation Reuse Framework for Satellite Edge Computing Networks |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2503.11946 |