# CubeSat Mission Scheduling Method Considering Operational Reliability
## 1 Introduction  
With the deepening of aerospace research, the demand for low-orbit space exploration missions and earth observation missions is increasing. Traditional satellites have disadvantages such as high costs and long research and development cycles. Compared with traditional satellites, CubeSats have the advantages of small size, low cost, and short development cycle and have great development potential in the aerospace field [1]. CubeSats have the basic functions of ordinary satellites, including attitude determination and control, satellite-ground communication, on-board data processing and storage, etc. [2]. Considering their short operating lifetime and limited energy-harvesting capability, it is necessary to formulate a reasonable task scheduling strategy for CubeSats. Satellite task scheduling is when the satellite management and control department allocates time windows and on-board resources for satellite tasks and formulates satellite in-orbit operation plans to maximize the value of missions under the premise of meeting various constraints [3]. Therefore, satellite task scheduling plays an important role in improving mission value and rationally allocating on-board resources. Satellite scheduling models are mainly divided into three categories: mathematical programming models (MPMs) [4, 5], graph theory models (GTMs) [6, 7], and constraint satisfaction problem models (CSPMs) [8, 9]. In the existing satellite mission scheduling research, the objective functions formulated include maximizing mission profit [10, 11], maximizing the sum ofmission priorities [12; 13], maximizing data throughput [14; 15], and maximizing image resolution in Earth observation (EO) missions [16]. In the research on satellite task scheduling models: Reference [17] analyzed the mission planning problem and transformed the satellite scheduling problem model into a knapsack problem model so that satellite task scheduling can be realized by solving the knapsack problem and thus the most basic mathematical model of satellite task scheduling problem is established; ref. [18] established a mission-planning model based on a general form of priority by studying the characteristics of satellite mission planning problems, without considering other indicators in the optimization direction; ref. [19] aimed at the single CubeSat mission planning problem and established a nonlinear programming model based on time window revenue without considering the constraints on the activation time and period of the satellite mission; ref. [20] studied the constraint satisfaction model for the collaborative planning of multi-satellite missions. The model can satisfy the attribute constraints of multiple satellites, extend the satellite mission scheduling model to multiple constellations, and reasonably allocate tasks according to resource attributes; ref. [21] designed a model for battery adjustment aiming at the mission planning problem of aging imaging satellites, and the satellite life was considered; ref. [22] constructed a mission-planning model for earth observation satellites that is more oriented to the scheduling of information transmission. The constraints in the model include satellite storage capacity limitations, data download rate limitations and task priorities, etc. ; ref. [23] gave four criteria (value, image quality, load balance of each satellite, task number) for evaluating the scheduling results and designed a multi-objective algorithm to solve the scheduling problem of satellites, representing an improvement in the algorithm; ref. [24] constructed a scheduling model using an integer-planning approach, considered parameters such as the priority and execution time of each task, and used the input power as a constraint but did not consider the task work in the shaded area due to the lack of a battery model.