With the development of space information network (SIN), new network applications are emerging. Satellites are not only used for storage and transmission but also gradually used for calculation and analysis, so the demand for resources is increasing. But satellite resources are still limited. Mobile edge computing (MEC) is considered an effective technique to reduce the pressure on satellite resources. To solve the problem of task execution delay caused by limited satellite resources, we designed Space Mobile Edge Computing Network (SMECN) architecture. According to this architecture, we propose a resource scheduling method. First, we decompose the user tasks in SMECN, so that the tasks can be assigned to different servers. An improved ant colony resource scheduling algorithm for SMECN is proposed. The heuristic factors and pheromones of the ant colony algorithm are improved through time and resource constraints, and the roulette algorithm is applied to route selection to avoid falling into the local optimum. We propose a dynamic scheduling algorithm to improve the contract network protocol to cope with the dynamic changes of the SIN and dynamically adjust the task execution to improve the service capability of the SIN. The simulation results show that when the number of tasks reaches 200, the algorithm proposed in this paper takes 17.52% less execution time than the Min-Min algorithm, uses 9.58% less resources than the PSO algorithm, and achieves a resource allocation rate of 91.65%. Finally, introducing dynamic scheduling algorithms can effectively reduce task execution time and improve task availability.

中文翻译：

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空间信息网络改进蚁群算法移动边缘计算资源调度

随着空间信息网络（SIN）的发展，新的网络应用不断涌现。卫星不仅用于存储和传输，还逐渐用于计算和分析，因此对资源的需求越来越大。但卫星资源仍然有限。移动边缘计算（MEC）被认为是减轻卫星资源压力的有效技术。为了解决卫星资源有限导致的任务执行延迟问题，我们设计了空间移动边缘计算网络（SMECN）架构。根据该架构，我们提出了一种资源调度方法。首先，我们将SMECN中的用户任务进行分解，使得任务可以分配到不同的服务器上。提出了一种改进的SMECN蚁群资源调度算法。通过时间和资源限制改进蚁群算法的启发因子和信息素，并将轮盘赌算法应用于路径选择以避免陷入局部最优。我们提出一种动态调度算法来改进合约网络协议，以应对SIN的动态变化，动态调整任务执行，以提高SIN的服务能力。仿真结果表明，当任务数量达到200个时，本文提出的算法比Min-Min算法减少17.52%的执行时间，比PSO算法减少9.58%的资源使用，资源分配率为91.65 %。最后，引入动态调度算法可以有效减少任务执行时间，提高任务可用性。