# Design and Evaluation of Dynamic Topology for Mega Constellation Networks
## 2 Related Works
### Dynamic Satellite Network Topology  
The typical dynamic link assignment policies are summarized as the following two policies. The first is generated based on the shortest distance strategy, while the second is based on the longest visible time strategy [10]. 1. Based on the shortest distance strategy. The central concept of the link selection strategy based on the shortest distance is that the source satellite selects the nearest target when choosing a satellite to establish an ISL. As the satellites constantly move at high speeds, the distance between each node must be continuously calculated, and their visibility analyzed to ensure link connectivity. When the source satellite detects a closer node, it adjusts the connection and establishes a new link with the nearest satellite. 2. Based on the maximum visible time strategy. According to the core idea of the link selection strategy derived from the longest visual time, the source satellite will give preference to the target with which it has the longest visual time when selecting satellites to establish an ISL. Once the link is established between the two satellites, the connectivity continues until the target satellite is out of the visual range of the source satellite, and the other satellite with the longest visual time is then reselected after the interruption. [PERSON] et al. [11] proposed a link assignment algorithm suitable for dynamic satellite networks, which optimizes the overall network topology connectivity. The algorithm enables rapid decision making on whether to establish or terminate links based on the time-varying state of the network. However, the algorithm is relatively complex and may not be feasible for prominent constellations. [PERSON] et al. [12] reviewed the dynamic routing algorithm based on virtual nodes and proposed using a low-complexity probability routing algorithm (LCPR) to solve the problem of selecting the next hop when the satellite receives the packet. By obtaining the location information of the source node and target node, the optimal path is obtained by using the distributed computing method, but the LCPR algorithm is only applicable to the polar orbit in the LEO satellite network. [PERSON] et al. [13] adopted a connection-oriented link allocation strategy aimed at reducing the vast network overhead caused by frequent routing table updates. Although this method can balance the network traffic, the network performance will be significantly reduced when the network topology loses its regularity. In another paper, [PERSON] et al. [14] developed an intelligent optimization algorithm that analyzes the dynamic network topology to determine the quality of experience of various regions and provide orbital parameters for satellite constellation configuration. However, the assumed demand distribution is static and overly idealized, which does not accurately reflect real-world user demand. [PERSON] et al. [15] developed a cost-effective, dynamic network for computing and proposed a heuristic algorithm to calculate link assignments for interstellar optical communication networks. However, the proposed method is limited to interstellar laser links and does not address scalability issues in prominent constellations. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Topology Type** & **Advantages** & **Disadvantages** \\ \hline Star topology [8] & Simple structure, easy to improve & Inability to achieve full coverage \\  & Simple structure, easy to improve & and heavy burden on \\  & & central nodes \\ Ring topology & Stable communications in the & Low communication efficiency \\  & coverage area & and poor scalability \\ Tree topology & Small diameter and efficient routing & Root nodes are heavily burdened \\ Mesh topology [9] & High reliability, high redundancy, & High cost, difficult to control \\  & low latency, many links & and inefficient \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Topology characteristics.