## 4 Routing in Integrated Networks
First, to model hot air balloons at various heights and elevation angles, researchers proposed an algorithm that determines multiple sub-traffic-matrices (STMs) using the water-filling method for a traffic matrix, representing the amount of traffic transferred between satellites. They then forwarded the data traffic indicated by the STMs to the appropriate target satellites, utilizing a carefully crafted configuration matrix generation algorithm. Finally, considering the constraints, such as the number of lasers and traffic delay, they obtained the optimal parameters to enhance the system's energy efficiency by using geometric programming and the Taylor series approach. The simulation results confirm the efficiency of the proposed approach. In addition, the scope of the study can be expanded by taking into account the scenarios of asymmetric time windows [123]. In 2022, [PERSON] et al. focused on an effective network governance and administration architecture for the ultra-dense LEO satellite-ground integrated network. This aimed to provide a more efficient and effective network control and management method for  
Figure 6: The setup of an SDN framework utilizing machine learning. the governance and administration of the network, which is quite complex due to the natural heterogeneous characteristic features, high dynamics, frequent changes in network situations over time, and the large number and density of satellites of ultra-dense LEO satellite-ground integrated networks. A hybrid multilayer network control and management framework was proposed for the ultra-dense LEO satellite-ground integrated network. This architecture includes the grouping and clustering methods of LEO nodes, and for each group, the MEO satellites and (CH) LEO satellites are designated as global and local controllers. In addition, different components, such as mobility management, network status control, resource management, and service management, are also included. The suggested hybrid network governance and administration architecture provides an effective management approach to the ultra-dense LEO satellite-ground integrated network. In particular, the identification of global and local controllers using grouping and clustering methods is a suitable solution for managing the large-scale and complex structure of the network. However, since the proposed method has not been tested with real-time data and in real application situations, its performance in real application situations is not clearly known [124]. In 2022, researchers focused on network slicing for unified satellite and ground networks in 6G networks. Given that computer networks are inherently dynamic and that there will be a growing number of connected devices in 6G, the management of satellite networks and network segments requires dynamic solutions. In one study, the researchers also used network slicing, which allows a physical network to be divided into multiple logical networks (slices) to assign resources and customize each slice to meet different service requirements and user demands. The proposed intelligent framework combines the resources of satellite and ground networks using network slicing and optimizes path selection with a machine learning algorithm similar to ant colony optimization, which can dynamically adapt to environmental changes. Using a centralized and distributed control plane, it performs both routing and slice management according to user demands. The performance results show that the proposed network slicing framework provides more efficient resource utilization than other strategies by accepting more user requests and saving priority routes for services that need them. The work can be improved by studying more satellite and base station scenarios, advanced machine learning algorithms, and different traffic profiles [125]. In 2024, [PERSON] et al. focused on the integration of LEO satellite communication and mobile edge computing (MEC) to improve internet access in remote areas.