# Offloading of Atomic Tasks in Satellite Networks:
## 1 Introduction
Therefore, the key to resolving the task offloading problem is to specify appropriate offloading decisions that measure the performance of the approach through time delay and energy consumption. The merit metrics of the offloading strategy can be determined based on the time consumption metrics of the scheme, which we call the minimizing cost offloading decision. There are still three challenges in solving the optimization problem of atomic task offloading in spatial information networks:  
Figure 1: Overview of the task offloading method. Although the time cost consumption of the traditional method is low, its performance cannot satisfy the high time-effective requirements for offloading atomic tasks in Spatio-temporal dynamic characteristics network environments. 2. The traditional satellite task offloading method does not consider the concept of inter-satellite collaborative computing, the inter-satellite resource coordination capability is low. 3. There is no optimization method for on-board task cache. This paper proposes an optimization model to address the Offloading and Caching of satellite atomic tasks based on the Maximum Flow method (OCMF) to address the above problems. The method mainly includes three sub-models: the maximum task flow transmission model, the task offload optimization model, and the task cache optimization model. To solve the problem of calculating the maximum number of unloaded atomic tasks for the joint transmission of multiple low-medium orbit satellites, the maximum task flow buffer model limits the atomic tasks scale upper limit that can be unloaded per satellite, ensuring the maximum number of unloaded tasks in the local satellite network. Task offloading optimization mainly includes two aspects: the optimization of task offloading from low-medium orbit satellites to high-orbit satellites, and the other is the optimization of task offloading from high-orbit satellites to low-orbit and medium-orbit satellites with idle resources. The model reduces the long-term waiting of atomic tasks so that when the satellite network benefits the most, the waiting time is consumed in the least. The task cache optimization model avoids the repeated calculation of many repeated atomic tasks and reduces the atomic task calculation time. Therefore, this paper mainly considers the maximum unloading of satellite atomic tasks and the full utilization of satellite resources, the reduction of the atomic tasks waiting time, and the reduction of atomic task calculation time, which provide new ideas for improving the efficiency and real-time performance of atomic tasks in satellite networks. Our contributions can be briefly summarized as follows:  
1. We propose the OCMF model, which divides the original problem into three parts and designs the maximum flow transmission, task offload, and task cache optimization models. 2. We introduce the maximum flow calculation method to increase the number of unloaded atomic calculation tasks in the satellite network. 3. We propose a method for high-orbit satellites to offload tasks to idle medium-earth satellites, which reduces the computational pressure of high-orbit satellites and makes full use of the remaining idle satellite resources. 4. We have analyzed and compared the performance of various algorithms. The OCMF method has certain advantages in terms of time complexity and task execution timeliness.