In this paper, we propose a double-edge-assisted computation offloading and resource allocation scheme tailored for space-air-marine integrated networks (SAMINs). Specifically, we consider a scenario where both unmanned aerial vehicles (UAVs) and a low earth orbit (LEO) satellite are equipped with edge servers, providing computing services for maritime autonomous surface ships (MASSs). Partial computation workloads of MASSs can be offloaded to both UAVs and the LEO satellite, concurrently, for processing via a multi-access approach. To minimize the energy consumption of SAMINs under latency constraints, we formulate an optimization problem and propose energy efficient algorithms to jointly optimize offloading mode, offloading volume, and computing resource allocation of the LEO satellite and the UAVs, respectively. We further exploit an alternating optimization (AO) method and a layered approach to decompose the original problem to attain the optimal solutions. Finally, we conduct simulations to validate the effectiveness and efficiency of the proposed scheme in comparison with benchmark algorithms.

翻译：本文提出了一种面向空天海一体化网络的双边缘辅助计算卸载与资源分配方案。具体而言，我们考虑一种场景，其中无人机与低地球轨道卫星均配备边缘服务器，为海上自主水面船舶提供计算服务。船舶的部分计算任务可通过多址接入方式同时卸载至无人机与低地球轨道卫星进行处理。为在时延约束下最小化空天海一体化网络的能耗，我们构建了一个优化问题，并提出能效优化算法，分别联合优化卸载模式、卸载量以及低地球轨道卫星与无人机的计算资源分配。进一步采用交替优化方法与分层策略对原问题进行分解以求得最优解。最后，通过仿真实验验证了所提方案相较于基准算法的有效性与高效性。