# Dynamic Routings in Satellite Networks: An Overview
## 4 Existing Works on Dynamic Satellite Routings  
Due to the constant movement of satellites and highly dynamic network topology, the inter-satellite routing algorithms have been the focus and challenges of satellite networks. Especially since 2015, the enthusiasm for its research has increased annually. In particular, subjects such as QoS, network topology, congestion control, and intelligent satellites make up the bulk of satellite routing researchers, as shown in Figures 3 and 4 [21]. Figure 4: The major studies inside the satellite routings. Figure 3: Number of articles. The dynamical characterization of the satellite network topology has been the focus of current research. As an emerging method, the temporal aggregation graph, is one of the most effective available tools. For satellite networks with limited resources, a resource allocation template was developed in [22]. With the assumption that the topology of each node stays unchanged, the model divides the period of the satellite network into several periods. The network topology for each time interval can be converted into a static topology graph. Given the unique \"receive-store-send\" mechanism of satellite networks, the scheme adopts the approach of storing arcs to connect the static maps of each timeslot to form a complete network structure. Although temporal aggregation graphs can solve the topology problem of dynamic networks well, it is difficult for the algorithm to adapt to long-term topological changes. As the graph grows, the work in [23] proposed a maximum flow algorithm based on storage time aggregated graph (STAG) to solve the maximum flow problem in disruption-tolerant networks (DTN). STAG utilizes DTN to build the model, incorporating the characteristics of DTN time-variation. In STAG, each node utilizes a bi-directional storage delivery sequence that reflects the correlation between data storage and edge-time gap. STAG can better reflect the time-varying satellite network characteristics, and it aggregates the characteristics of link connections and satellite nodes, resulting in a less complex temporal aggregation graph that takes up less storage resources. In addition, the maximum traffic STAG technology is able to use limited satellite network resources to deliver massive amounts of data services efficiently. In a given topology, routing is an essential metric determining network performance. The growing size and complexity of satellite networks, however, has made onboard routing more challenging. Various improved routing algorithms have been proposed in academia in response to these problems. Multi-path routing can greatly improve network throughput and end-to-end delay. Using a network-coding-based multi-path routing approach, the complex coordination problem between multiple paths is resolved, thereby improving the data transmission efficiency. In the end, the work in [24] presented a network-coding-based multi-path cooperative routing protocol (NCMCR) to improve the throughput of the LEO satellite networks. The scheme provides a multi-path cooperative routing algorithm that enables dynamic data transmission along multiple paths. The work in [25] employed a time-domain grid model (TNM) to describe the time-varying topology of a large-scale network of small satellite networks (SSNs). The scheme replaces the traditional coordinate positioning method, and satellites can be positioned by the grid. The scheme proposes an efficient grid shortest path routing (NSR) algorithm based on TNM. The work in [26] further investigated the problem of large-scale heterogeneous Internet interference-resisting routing. Firstly, a Stackelberg-based routing strategy for resilience to interference is proposed. Secondly, a deep-reinforcement-learning-based routing algorithm (DRLR) method is used to train it with deep enhancement. Then, a fast response anti-jamming algorithm (FRA) is given to perform anti-jamming decisions.