# Dynamic Routings in Satellite Networks: An Overview
## 2 Related Works
At the same time, LEO satellites are source and relay nodes, so the routing algorithm must respond to load and link-state changes. Simulation findings show that the approach balances the service load, decreases link congestion and packet loss, and enhances the LEO satellite network's throughput. In conclusion, the algorithm outperformed ELB and TLR algorithms in terms of effective network traffic load balancing. In particular, the algorithm improves LEO network performance by reducing packet loss and increasing throughput under load. In addition, the authors also investigated a connection congestion notification and rerouting strategy. A comparison of the partial routing algorithms mentioned is shown in Table 1.  
The work in [13] provided a detailed description of the architecture of the space-air-ground integrated network (SAGIN) and immersive media (IM) services. The literature on the SAGIN architecture was explicitly introduced, and its architecture, advantages, and critical indices were reviewed. The SAGIN literature review is divided into three sections. The authors investigated resource allocation and communication methods in diverse networks in the first category. Second are the SDN-based SAGIN designs for intelligent management and orchestration. Third are the SAGIN architectures in specific application contexts. IM is an emerging service model whose virtual nature has attracted the attention of most scholars. However, IM has the drawbacks of having excessive bandwidth, a low transmission rate, and high latency regarding network performance. Then, to address the issue, the authors proposed the service customized SAGIN architecture for IM (SAGIM) based on the Service customized network (SCN). The integrated network is the core component of SAGIM. It consists of a space segment, an air segment, and a ground segment. The space segment includes GEO and LEO satellites. They communicate with each other via microwave or laser. The LEO satellites support broadband Internet access for IM services. The solution further designed the functional components of SAGIM, including the infrastructure layer, sensing layer, intelligence layer, and application layer, to enable intelligent network management. As the core foundation of the SAG-IM architecture, the infrastructure layer provides the fundamental guarantee for the operation of the integrated network. The network infrastructure includes the network entities and links that ensure the robustness of the network. To separate services for different users, hardware resources are divided into communication, computing, and storage resources. These virtual resources provide data processing and transmission for different services in the network. The sensing layer is used to collect the network state of the infrastructure layer, including node and link information, etc. The intelligence layer is the brain of the SAGIM architecture and is responsible for scheduling network resources. In addition, the Intelligent layer load establishes routing and forwarding strategies to assure QoS for other IM requests. The application layer ensures SAGIM's efficient functioning and flexible network setup. In particular, to improve the intelligent management of the network, the processing of the application layer is outlined in detail. The authors also analyzed the clustering technology of multi-tier SDN controllers and the deployment technology of edge servers. The layered SDN controller deployment policy implements intelligent routing, throughput control, load balancing, etc. SAGIM controllers are placed in ground data centers and satellites, improving the update and configuration performance. As SAGIN has some limitations in instant messaging services, to enhance the user experience, key technologies for intelligent routing and delivery were further discussed in the paper. Finally, the author analyzed and summarized the research directions and potential technical challenges of SAGIM in future applications.