# DRL-Based Dynamic SFC Orchestration Algorithm for LEO Satellite Networks
## 2 Related Works  
Research on SFC orchestration, migration, and related domains in terrestrial networks has been extensive and multifaceted. Scholars have proposed various solutions employing heuristic algorithms and artificial intelligence to address emerging challenges in these environments. In NFV-enabled SDN environments, reference [12] explored VNF instance selection and placement strategies for SFC request routing, validating their approach through NSFNET network simulations. Reference [13] demonstrated the efficacy of their proposed SFC deployment methodology in networks comprising dozens of nodes and links. Reference [14] examined wireless-aware SFC deployment in industrial Internet contexts with edge computing capabilities, incorporating wireless-aware deployment parameters into the SFC deployment framework. The characteristics of different network environments significantly influence SFC deployment strategies. In SDN data center networks, static topologies with relatively few nodes and links operate under less stringent delay constraints. IoT networks, while more numerous in nodes, primarily exhibit this complexity in access and edge nodes, featuring high-degree access nodes and hierarchical structures. These networks are characterized by functionally differentiated physical nodes and primarily access point mobility. In contrast, LEO satellite networks present unique challenges: dense, homogeneous satellite distributions, larger problem scales, and time-varying topological characteristics. The dynamic nature of orbital motion affects all links, while constellation movement influences SFC access and exit nodes, necessitating distinct research approaches. The evolution of satellite networks has followed a unique trajectory, resulting in comparatively limited research in this domain. The inherent dynamism and resource constraints of satellite network topologies present significant challenges to the direct application of terrestrial SFC orchestration algorithms. Several studies have addressed real-time physical resource coordination in dynamic networks through innovative VNF mapping algorithms. Reference [15] enhanced the connected vehicle service acceptance rates in SGIN through real-time VNF migration and rescheduling mechanisms. Reference [16] developed a dynamic VNF mapping algorithm considering satellite power limitations and ISL rate constraints. Reference [17] introduced a heuristic approach that effectively reduces computational complexity while improving service success rates. The deployment of single-user VNFs in satellite networks requires careful consideration of dynamic topology impacts. Reference [18] addressed this challenge by formulatingVNF deployment and traffic routing as a multi-slot integer linear programming problem, proposing a heuristic solution that minimizes network overhead while accommodating topological dynamics through temporal evolution. Reference [19] presented an integrated algorithm combining Dantzig-Wolfe decomposition, column generation, and branch-and-bound techniques to optimize inter-satellite link resource utilization, though its computational complexity limits application in large-scale networks. Reference [20] introduced an innovative approach that incorporates dynamic topology, resource constraints, and QoS requirements into VNE problem constraints, proposing heuristic solutions. Reference [21] conceptualized SAGIN resource allocation as a Markov decision process, developing a distributed deep reinforcement learning architecture for VNF resource management. Reference [22] formulated the optimization challenge as a potential game, introducing distributed resource allocation algorithms that balance deployment cost minimization with service user maximization. While these algorithms demonstrate effectiveness within their specific domains, they do not adequately address the sequential constraints between virtual network functions--a critical factor that directly impacts service outcomes.