# Dynamic Network Resource Autonomy Management and Task Scheduling Method
## 2 Related Work  
With the continuous development of satellite applications [3], the satellite industry is also undergoing a revolution, and in the context of current 5G network applications [3; 7; 8], how to provide faster data transmission rates, low-latency services, etc. [9; 10; 11; 12], and how to efficiently and effectively It is particularly important to plan, coordinate, and execute satellite scheduling and tasks under limited resources [13; 14; 15], and to maximize the efficiency of resource use while ensuring that all tasks are met [2; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28]. For the problems in traditional satellite network scheduling, such as limited satellite resources, coordination between multi-level scheduling, satellite interference, and how to effectively handle the interaction between satellites and networks, these problems will also lead to satellite resource utilization [29; 30; 31]. In scheduling satellites, the imbalance between scheduling and information transmission will cause the network performance to be not very high [20; 32]; some parameters are not Meets expectations, such as transfer delays between networks and the rate at which messages are delivered [11]. Aiming at the insufficient resource utilization and application problems in satellite task scheduling, [PERSON] et al. proposed a software-defined satellite network architecture (SDSN). The architecture is designed to simplify networking between multifunctional satellites and provide higher resource utilization. SDSN uses a new protocol to enable testing and deployment to achieve this goal. After testing, the seamless handover mechanism of SDSN has significantly improved handover delay and throughput. However, although SDSN supports flexible low-level protocols, it fails to adapt to some high-level protocols [7; 33; 34]. This means that SDSN may be unable to meet some specific applications' needs. Therefore, in future development, SDSN may need to provide more protocol adaptation functions to meet a broader range of application scenarios. [PERSON] et al. proposed a method for achieving fair performance among user satellites, a mixed-integer nonlinear program optimization problem. To solve this problem, they decompose it into two equivalent subproblems. Among them, the task scheduling problem of optimal power allocation is also a mixed integer linear programming problem. Experimental results show that this algorithm has certain advantages in solving task scheduling problems [35; 36]. Although this algorithm performs well in some cases, it may face convergence difficulties when dealing with large-scale problems. SoftSpace, proposed by [PERSON] et al., is a new generation of satellite network software-defined architecture, which adopts concepts such as network function virtualization and aims to reduce capital and operating costs and improve the interoperability of satellite network equipment [2; 37; 38]. However, although SoftSpace excels in many ways, it has some challenges, such as security issues and controller selection issues that have not yet been resolved. These issues are the critical points that SoftSpace needs to pay attention to in future development. [PERSON] et al. proposed a throughput-maximizing mixed-integer linear programming approach to solve the problem of low throughput and joint management between energy and transponder resources in small satellite networks. The method uses a scalable time-evolution graph to describe network resources and experiments with high throughput on a time-slot basis. Simulation results show that this method can achieve high throughput with low complexity [36]. However, although this method performs well in ensuring efficient use of the network, it does not consider the priority among multiple tasks and the reliability issues among the various links of satellite scheduling [39]. The cross-domain SDN architecture proposed by [PERSON] et al.