# Dynamic Routings in Satellite Networks: An Overview
## 4 Existing Works on Dynamic Satellite Routings
### Dynamic Routings in the Multi-Layer Satellite Networks
#### 4.2.3 Traffic Balancing Dynamic Routings
Additionally, as each LEO satellite covers a smaller area, the unbalanced intensity of service demand in multi-layer networks may cause more severe link congestion and longer queuing delays. Therefore, actors such as congestion and queuing delay need to be added when designing the routing scheme for dynamic traffic balancing. Based on the prediction of traffic distribution, the work in [103] presented a parametric adaptive multi-attribute decision making (PASMAD) access and switching algorithm for GEO-LEO heterogeneous satellite networks. The algorithm customizes a dynamic parameter to balance the network load and solve link congestion caused by uneven traffic distribution in heterogeneous networks. In addition, for the improved approach, the throughput of the entire heterogeneous network can be boosted while ensuring the QoS for users. The method fails to optimize the satellite network's topology and reduces its fast conversion capability to improve communication performance. Furthermore, since the algorithm adopts real-time data collection to complete the routing operation, a corresponding load balancing mechanism is omitted. As network complexity increases, multi-layer satellite network service requirements grow, causing a high packet loss rate and long queuing delay. Additionally, as each LEO satellite covers a smaller area, the unbalanced intensity of service demand in multi-layer networks may cause more severe link congestion and longer queuing delays. Therefore, congestion and queuing delays must be added to the routing scheme for dynamic traffic balancing. In 2019, the work in [104] investigated a new routing update method. The method accurately detects queuing delays and dynamically adjusts routing paths according to queue changes. The solution can predict link conditions before congestion occurs on the link and reasonably select suitable routes based on various traffic situations in the link. Consequently, all satellites in the network have more possibilities to receive packets from neighboring satellites, solving the traffic congestion issue of the next hop in satellite nodes to some extent. Moreover, in a multi-layer satellite network, multiple satellite nodes need to transmit data simultaneously. However,the limitation of the storage resources of the satellite network can make the data among the nodes conflicting. To better allocate the service resources in the satellite network, the work in [105] adopted a routing method based on game theory and distributed cache negotiation. The approach proposed a new competition model for LEO satellite traffic to maximize the use of traffic resources. Furthermore, Stackelberg traffic balance routing uses a threshold function to convert non-convex optimization into convex optimization. However, the method has limitations to routing and data relaying, which causes transmission delays and packet losses. The balanced dynamic routing of traffic in multi-layer satellite networks requires the ability to predict and analyze end-to-end traffic. In 2020, the work in [106] designed a communication architecture with an energy metering node (EGN) at its core. The scheme developed a unified traffic balancing strategy for resource-limited multi-layer satellite networks. The approach ensures that the network remains operational for the maximum possible time, extending the lifetime of multi-layer satellite networks. However, the algorithm is based on a grid-type satellite network with a static and relatively time-invariant topology. For multimedia services, user satellites are not consistently grouped in small clusters, so grid-based traffic allocation methods are no longer applicable. Link overload traffic in densely populated areas can easily cause network delays and throughput crashes due to satellites' geographical limitations. An effective traffic-congestion-aware routing scheme is indispensable to ensure the communication quality of multi-layer satellite networks. Therefore, in 2021, the work in [107] proposed a traffic-balancing strategy based on a hybrid satellite network.