## 3 Dynamic Multi-Reporting Nodes Selection Method  
In LEO satellite networks, the length of the end-to-end service path is relatively long, and the single-node reporting method can lead to significant awareness delay and overhead due to multi-hop accumulation. Therefore, multiple reporting nodes need to be selected for segmented reporting. When the INT method is applied to terrestrial networks, a fixed hop interval approach is commonly employed to select multiple reporting nodes, due to the relative stability of terrestrial network nodes and links. However, when applied to satellite networks, such methods may result in significant cumulative awareness delays due to unstable ISLs and may also prevent timely reporting of awareness data due to the intermittency of SGLs. In this section, a dynamic multi-reporting nodes selection method of network awareness based on the APINT model is proposed, which can select the optimal number and location of reporting nodes for the awareness path. The procedure for selecting multi-reporting nodes is illustrated in Figure 3. The selection of the optimal reporting node requires consideration of both the number of reporting nodes and the length of their respective intervals, as both factors jointly influence the telemetry time of the awareness path and the specific location of the reporting node. The issue of selecting multiple reporting nodes can be converted into an interval partitioning optimization problem. Therefore, the concept of virtual boundaries is introduced, dividing the multi-hop path P\({}_{z}\) into Y segments, with the set of virtual boundaries for all segments represented as \(V=\{V_{1},V_{2},\ldots,V_{Y}\}\), where the number of satellites in each segment is \(N_{\text{V}}\)\(=\{N_{\text{V1}},N_{\text{V2}},\ldots,N_{\text{VY}}\}\). Using each segment as the optimization object, the best reporting node is searched for within each segment based on the APINT model. Specifically, upon reaching the virtual boundary starting point of the segment, the service initiates passive telemetry along the route. Conversely, upon reaching the virtual boundary endpoint, it  
Figure 3: Procedure for multi-reporting nodes selection. Figure 2: Telemetry and reporting process of APINT. sends active telemetry packets, which are aggregated and reported at the optimal reporting node within the segment. Then the service proceeds to transmit and enter the subsequent segment, repeating the process until it arrives at the target node. However, the division of different virtual boundaries results in different reporting node selection results, necessitating the selection of the optimal solution from numerous results. Therefore, by considering the awareness time within segments, awareness overhead of segments, and the number of reporting nodes, an awareness evaluation function is constructed. The optimal telemetry and reporting solution for the path is determined by the minimum number of reporting nodes and their respective locations, as indicated by the awareness evaluation function across various scenarios involving different virtual boundary segmentations. The optimization objective function is:  
\[\text{min~{}Eva}= \beta\cdot\text{F}(Y)+\delta\cdot\text{F}(\overline{\text{T}_{ \text{V}}^{2}})+\tau\cdot\text{F}(\text{E}_{\text{Vi}}), \tag{10}\]  
where \(\beta\), \(\delta\), and \(\tau\) are the corresponding optimization weights, with \(\beta+\delta+\tau=\)1. The function of F is the normalization function. \(\overline{\text{T}_{\text{V}}^{2}}\) is the average awareness time of segments. \(\overline{\text{E}_{\text{Vi}}}\) is the average awareness overhead of segments. The specific calculation is as follows. The telemetry and reporting time for each segment after selecting the optimal reporting node based on the APINT model are \(\text{T}_{\text{V}}\)\(=\)\(\{\text{t}_{\text{V1}},\text{t}_{\text{V2}},\dots,\text{t}_{\text{VY}}\}\).