# Dynamic Routings in Satellite Networks: An Overview
## 4 Existing Works on Dynamic Satellite Routings
### Dynamic Routings in the Multi-Layer Satellite Networks
#### 4.2.2 QoS-Based Dynamic Routings
Finally, the effectiveness of the algorithm is verified by theoretical analysis. However, the model fails to consider the requirements of task transmission and cannot give a specific QoS routing scheme. Therefore, in 2019, the work in [81] engineered a QoS multiple routing (QSRR) algorithm. The algorithm focuses on the QoS issue for multiple transmission tasks on multi-layer satellite networks. The proposed algorithm considers traffic and delay requirements based on time-varying network resources. However, the algorithm leaves out the effect of the satellite transceiver on the routing performance. Therefore, future research can focus on QoS routing with limited transceiver resources. In multi-layer satellite networks, the rapid growth in the type and volume of services has made the QoS requirements of users even more demanding. Traditional QoS routing algorithms consider only a single QoS demand, ignoring their priority relationship, which affects network resource utilization. In 2018, the work in [82] exploited the feature vector method to set weights for varied QoS state values. The link evaluation index is composed of the priority function and the evaluation criterion function, and the optimal path that meets the QoS requirements is solved. The algorithm uses a GEO satellite as the link information controller and an LEO satellite to update the link information in orbit. The simulation results show that the algorithm effectively solves the QoS guarantee issue of multi-media resources under a large load. In addition, the algorithm can distinguish different QoS requirements and balance network traffic, further improving network resource utilization. However, the algorithm fails to guarantee the QoS of data transmission. Based on this, making use of the ant colony algorithm, the work in [83] designed a dynamic QoS routing scheme (SRADR). The method improves and optimizes the heuristic approach to meet the communication requirements of multi-layer satellite networks. SRADR sends N ants from the source node to the destination node to find the best QoS path. The algorithm primarily consists of two processes: dynamic route lookup and dynamic routing table updates. Based on the optimization objective function, dynamic route finding is used to seek out the best path to different destination nodes. In multi-layer satellite networks with high dynamics and heavy performance jitter, SRADR requires setting a dynamic route detection cycle. During the period, a number of ants can be used to discover the optimal path to different destination nodes, and complete the dynamic update of the routing table. Based on the ant colony algorithm, in 2019, the work in [84] designed a QoS routing algorithm using the ant colony algorithm. The average delay of the algorithm is measured in seconds, the latency jitter of each path is measured in milliseconds, and the packet loss rate of each path is only 0.11%, which guarantees the QoS requirements of multi-layer satellite networks. However, the algorithm guarantees the QoS requirements by sacrificing the satellite network communication overhead. Meanwhile, the authors proposed a multi-constrained QoS routing algorithm for multi-layer satellite networks. Utilizing the QoS information in the current link as an essential basis for ants to select the next-hop node, the algorithm enhances the heuristic function of the ant colony algorithm. In the LEO-MEO-GEO satellite network, the time division routing protocol (TDRP) is applied to classify the satellites in various layers [85]. Each layer of satellites can be treated independently, saving computing time. In particular, the GEO satellites are responsible for the routing table calculation and are entirely independent. In addition, after calculating the routing table for their respective layers, MEO and LEO satellites must send it to their group members, making them relatively independent.