###### Abstract
At the same time, link information from a period of time before the topology change occurs, and in a specific area, can be collected in a targeted manner. This can not only improve the accuracy of the algorithm, but also prevents a large amount of routing overhead from transmitting link information. For the LEO satellite system transmission network, in addition to sun outage, the predictable topology changes mainly include changes in the propagation delay of inter-satellite links, switching of inter-satellite links in polar regions, and feeder links between ground stations and satellites. To solve the above problems, there are strategies such as virtual topology and virtual nodes. These strategies are aimed at generating the whole network topology and simply using the link cost method to calculate the whole network route. The virtual topology strategy [6] is suitable for complex network structures and changing network topologies. The network topology is stored in slices in each satellite, which avoids a large amount of routing information interaction and routing calculations, but it also requires satellites to have certain storage capabilities [7]. The virtual node strategy [8] takes advantage of the periodicity of topology changes and avoids the need for storage, but it is only applicable to polar-orbit LEO constellations and requires high regularity in the satellite network topology. Among them, the virtual topology strategy can help satellite nodes deal with topology changes caused by sun outage failure. At the same time, a load-balancing algorithm needs to be designed to solve the congestion problem that may be caused by link failure. In this paper, we designed a sun-outage-recovery algorithm for LEO satellite inter-satellite links based on virtual topology, which collects network information in the area where the link is about to fail during a period of time before the sun outage occurs. The traffic in the failed link is redistributed to achieve load balancing in the failed area during sun outage. The contributions of this article include: \begin{table}
\begin{tabular}{c c} \hline
**Acronym** & **Definition** \\ \hline LEO & Low earth orbit \\ ISL & Inter-satellite link \\ LPRA & Local pre-rerouting algorithm \\ AQM & Active queue management \\ DSP & Dijkstra shortest path \\ STK & Satellite tool kit \\ QoS & Quality of service \\ SPF & Shortest path first \\ IADR & ISL attributes-based dynamic routing \\ \hline \end{tabular}
\end{table} 
Table 1: Acronym list. Taking a typical polar-orbiting LEO satellite network system as the analysis object, the sun outage phenomenon in the inter-satellite link of the LEO satellite network was simulated, and the duration, location and occurrence pattern of sun outage failure of the inter-satellite link were analyzed. 2. A local pre-rerouting algorithm (LPRA) is proposed. This algorithm only collects link information in a limited area and performs centralized routing calculations, which solves the load-balancing problem in LEO satellite networks during sun outage. 3. An algorithm for uplink satellite reselection based on feeder link load and minimum hop count is developed, and the scalability of this algorithm in multi-layer satellite networks and large-scale constellations is discussed. The remainder of the article is structured as follows. First, the system architecture and traffic model of the LEO satellite network are introduced, then the simulation analysis of the sun outage phenomenon in the satellite system is performed, then a routing algorithm to solve the sun outage failure is proposed, and finally the algorithm performance is analyzed through network simulation.