Multi objective reinforcement learning driven task offloading algorithm for satellite edge computing networks
Abstract Satellite edge computing (SEC) has become a revolutionary paradigm to improve the quality of service, reduce the pressure on satellite-terrestrial backhaul bandwidth and reduce the average response delay of task requests. In this paper, we propose a task offloading algorithm based on K-D3QN...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-10553-6 |
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| author | Sai Xu Jun Liu Jiawei Tang Xiangjun Liu Zhi Li |
| author_facet | Sai Xu Jun Liu Jiawei Tang Xiangjun Liu Zhi Li |
| author_sort | Sai Xu |
| collection | DOAJ |
| description | Abstract Satellite edge computing (SEC) has become a revolutionary paradigm to improve the quality of service, reduce the pressure on satellite-terrestrial backhaul bandwidth and reduce the average response delay of task requests. In this paper, we propose a task offloading algorithm based on K-D3QN to meet the rapidly growing demand of ground users. This algorithm improves the DQN algorithm by incorporating a satellite resource clustering module, a DDQN algorithm, and a competitive network mechanism module. The offloading decision-making process comprehensively considers three optimization objectives: task latency, resource utilization, and load-balancing degree, to achieve dynamic multi-objective optimization. Experimental results shown that the algorithm significantly reduces task latency, improves resource utilization and load-balancing degree. |
| format | Article |
| id | doaj-art-44d34a01a2c34451aff35347a07fc36a |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-44d34a01a2c34451aff35347a07fc36a2025-08-20T03:45:26ZengNature PortfolioScientific Reports2045-23222025-07-0115111310.1038/s41598-025-10553-6Multi objective reinforcement learning driven task offloading algorithm for satellite edge computing networksSai Xu0Jun Liu1Jiawei Tang2Xiangjun Liu3Zhi Li4School of Computer Science and Engineering, Northeastern UniversitySchool of Computer Science and Engineering, Northeastern UniversitySchool of Computer Science and Engineering, Northeastern UniversityCS&S Information System Engineering Co.,Ltd School of Information Science and Engineering, Shenyang Ligong UniversityAbstract Satellite edge computing (SEC) has become a revolutionary paradigm to improve the quality of service, reduce the pressure on satellite-terrestrial backhaul bandwidth and reduce the average response delay of task requests. In this paper, we propose a task offloading algorithm based on K-D3QN to meet the rapidly growing demand of ground users. This algorithm improves the DQN algorithm by incorporating a satellite resource clustering module, a DDQN algorithm, and a competitive network mechanism module. The offloading decision-making process comprehensively considers three optimization objectives: task latency, resource utilization, and load-balancing degree, to achieve dynamic multi-objective optimization. Experimental results shown that the algorithm significantly reduces task latency, improves resource utilization and load-balancing degree.https://doi.org/10.1038/s41598-025-10553-6Space-based information networkSatellite edge computingTask offloadingReinforcement learningDQN |
| spellingShingle | Sai Xu Jun Liu Jiawei Tang Xiangjun Liu Zhi Li Multi objective reinforcement learning driven task offloading algorithm for satellite edge computing networks Scientific Reports Space-based information network Satellite edge computing Task offloading Reinforcement learning DQN |
| title | Multi objective reinforcement learning driven task offloading algorithm for satellite edge computing networks |
| title_full | Multi objective reinforcement learning driven task offloading algorithm for satellite edge computing networks |
| title_fullStr | Multi objective reinforcement learning driven task offloading algorithm for satellite edge computing networks |
| title_full_unstemmed | Multi objective reinforcement learning driven task offloading algorithm for satellite edge computing networks |
| title_short | Multi objective reinforcement learning driven task offloading algorithm for satellite edge computing networks |
| title_sort | multi objective reinforcement learning driven task offloading algorithm for satellite edge computing networks |
| topic | Space-based information network Satellite edge computing Task offloading Reinforcement learning DQN |
| url | https://doi.org/10.1038/s41598-025-10553-6 |
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