# A Computation Offloading Strategy in LEO Constellation Edge Cloud Network
## 2 Related Works  
At present, there has been some research on LEO satellite edge computation, mainly focusing on how the computation task makes the offloading decision between the satellite and satellite terminals. For example, in the multi-user single-satellite access scenario, [PERSON]. [6] established the LEO computation offloading model based on the joint optimization of system energy consumption and user delay and used the Nash equilibrium method of game theory and the Lagrange multiplier method of convex optimization to solve the optimal offloading strategy, step by step. In the multi-user and multi-satellite access scenario [7] proposed a two-layer computing offloading scheme integrating the satellite and the satellite terminal. The problem was formulated to an allocation problem, and the improved Hungarian algorithm was used to solve the problem. Simulation analysis was carried out from the two dimensions of reducing the task average delay and system energy consumption; [PERSON]. [8] proposed a three layer architecture for multi-user multi-satellite computing offloading scheme, including terrestrial users, satellite and ground cloud services, which considers single satellite coverage time and limited in-orbit computing power. The offloading decision was solved from the perspective of minimizing the total energy consumption of ground users. First, by adopting a relaxation method, the nonconvex problem is converted into a linear programming problem. Then, a distributed solution for large-scale networking is proposed based on the ADMM method. In [4], considering the dynamic characteristics of the satellite, the communication time between offloading satellite and ground user was limited, the model for the ground user and satellite was established based on queuing theory, taking the average response time and average energy consumption of a single task as optimization objectives, and the only optimal offloading strategy was obtained based on the Nash equilibrium in game theory. In the above literature, the LEO edge computation offloading strategy mainly uses the access satellite or access satellites' neighbors. Although the over-top satellite can provide the lowest delay, due to the limitations of satellite-carried devices in a space environment, volume, weight, energy and other aspects, the processing capacity of a single satellite is very limited, unable to serve enough users, resulting in the number of users being limited. On the other hand, due to the uneven distribution of users, overtop satellites are used in user-dense areas, which results in too few satellite computing resources allocated and an increase in the response delay of a single user. The researchers gradually realized the possibility of using the LEO constellation network to provide edge computing services and developed some preliminary ideas. In [5], a satellite-ground integrated edge computing network architecture (STECN) was proposed, in which the LEO satellite network deployed on the MEC platform was included, and its system architecture, collaborative offloading process, functional composition, and challenges and problems were described in detail. Ref. [3] discussed the possibilities and challenges of providing satellite-borne cloud computing services on a new generation of mega constellations, and discussed three application cases that can benefit from them, one of which is edge computing. In [9], the edge computing architecture of low-orbit constellation communication network was designed, but only one satellite orbit was considered in the modeling, and the offloading range was limited to the satellite within two hops from the user. A summary of the literature is listed in Table 1.  
Inspired by the above facts, this paper proposes an edge computing resource allocation strategy in a mega LEO constellation, which considers the unified arrangement of the energy resources and computing resources of the entire LEO constellation. A shared LEO constellation resource pool is formed for dynamic use by all users.