Collaborative Fault Tolerance Computing for Emergency Tasks in Lunar Radiation Environment

With the rapid development of lunar exploration, devices deployed on the lunar surface will encounter emergency events including meteor impacts and lunar dust storms. Additionally, the extreme lunar environment characterized by intense radiation and the high latency of Earth-based cloud computing pose severe challenges to real-time and reliable task processing. Existing collaborative computing and fault-tolerant schemes are not fully efficient in dynamic radiation environments. To address these challenges, a collaborative computing architecture integrating lunar surface devices and lunar orbit satellites is proposed for lunar emergency tasks. Comprehensive network, radiation, communication and computing models are established to support this architecture. The problem is then formulated as a multi-objective optimization problem and solved by the Radiation-aware hiErarchical collAborative Fault-Tolerant Reinforcement Learning (REAFTRL) algorithm, which integrates radiation-aware, hierarchical decision-making, and fault-tolerant execution with feedback mechanisms. Simulations show the proposed collaborative computing scheme outperforms traditional fault-tolerant strategies in task completion time, completion rate, and error rate, providing a reliable solution for future lunar exploration.