# Dynamic Routings in Satellite Networks: An Overview
## 4 Existing Works on Dynamic Satellite Routings
### Dynamic Routings in the Multi-Layer Satellite Networks
#### 4.2.1 SDN-Based Dynamic Routing
In multi-layer satellite networks, a large number of satellites and the dynamic topology make the multi-path transmission control protocol (MPTCP) the preferred routing protocol. To address the existing issues of the MPTCP, in 2018, the work in [61] proposed an SDN-based MPTCP routing algorithm. The solution determines new satellite routes by  
Figure 9: Routing process of SDN. using each link's remaining bandwidth, solving the \"bottleneck\" problem, and adapting to changing network loads. In addition, by adjusting the shared satellite links, the throughput of the network is further enhanced. To achieve more flexible traffic scheduling and QoS guarantees in multi-layer satellite networks, the work in [62] proposed an integrated framework for satellite-ground satellite communication networks (SERvICE). On this basis, two heuristic algorithms, the QoS-oriented satellite routing (QSR) algorithm and the QoS-oriented bandwidth allocation (QBA) algorithm, are designed to ensure the QoS requirements of multiple users. Inspired by the network framework, in 2019, the work in [63] presented a three-layer SDN-based satellite network model. The GEO satellite was the control satellite tasked with calculating the optimal communication link and resource allocation. Meanwhile, to improve the self-adaptive capability of the network, the GEO satellite can adjust the inter-satellite links in real time based on the network status. In addition, the scheme investigates an adaptive routing algorithm (ARA) based on the model. The algorithm finds the shortest communication path between satellites and optimizes the routing in real-time. The work in [64] combined machine learning and an SDN to solve dynamic network topology and link traffic awareness in multi-layer satellite networks. The scheme adopts the deep deterministic policy gradient (DDPG) algorithm for routing optimization. The algorithm can make appropriate routing decisions based on the real-time link state. In particular, utilizing the long short-term memory (LSTM) neural network, the algorithm improves the sensing capability between the associated satellite links. With the network controller control center (NOCC), the SDSN provides flexible configuration and scheduling for satellite nodes within the network. This significantly lessens the complexity of the satellite network architecture, onboard storage, and computational power requirements, especially for LEO and MEO onboard storage and computing. The SDSN is a new type of hybrid control network. Due to the excessive distance between the inter-satellite links, dynamic routing is challenging to adapt to the requirements of the network, especially for delay-sensitive services. Therefore, in SDSN, using the snapshot routing algorithm is still the most dominant path choice. However, the traditional snapshot routing method causes the GEO satellites to become more computationally intensive and results in the loss of data. In addition, it is inconceivable to accurately describe the topology of inter-satellite links due to the traditional snapshot routing. To ensure minimal computing power and storage pressure on GEO satellites in SDN systems, optimizing routing performance in dynamic topologies has become an urgent need for large-scale multi-layer satellite networks. In 2020, the work in [65] designed an adaptive snapshot routing strategy (ASRS) to optimize snapshot routing performance. ASRS is divided into two main categories. One is for the snapshot segmentation of multiple domains, and the other is the snapshot routing for various services. First, a multi-domain snapshot partitioning method is used to obtain each region's set of snapshot sequences. Then, the snapshot routing algorithm is employed. Satellite links select and combine snapshots based on service arrival and transmission times. ASRSs can effectively reduce the bandwidth resource loss of the channel. Simultaneously, the efficiency of snapshot routing has been improved.