With the rapid development of Internet of Things (IoT) technologies, the massive generation of data has posed significant challenges to traditional cloud computing models, particularly in terms of high latency and energy consumption. As a result, edge computing has emerged as a promising solution. However, in remote or disaster-prone areas, the lack of terrestrial communication infrastructure limits the deployment of edge computing. Satellite communication networks, with their wide coverage and independence from geographical constraints, offer an effective solution to this issue. In this paper, we propose a “UAV-LEO” system framework, where UAVs and Low Earth Orbit (LEO) satellites are utilized as edge computing nodes. We employ an intelligent optimization algorithm to optimize task offloading decisions and incorporate an adaptive checkpointing mechanism to enhance system fault tolerance. Experimental results demonstrate that the proposed method effectively reduces task completion time and energy consumption while significantly improving system reliability.