# Dynamic Network Resource Autonomy Management and Task Scheduling Method
## 4 Simulation Experiments
### Numerical Comparative Analysis
Therefore, our proposed algorithm is not too high in terms of computational and algorithmic complexity, and the algorithm is also simple and computationally efficient, which can process data quickly and complete the satellite scheduling task. Secondly, our proposed algorithm is highly flexible. It can adapt to the dynamic changes of the satellite scheduling task, thus shortening the time to complete the task and improving the system's efficiency. \begin{table}
\begin{tabular}{c c c c c c c} \hline  & **DUNM** & **PS** & **DS** & **NS** & **Barrier** & **Sifting** \\ \hline D1 & 0.465873 & 0.813586 & 0.841538 & 0.796589 & 0.802961 & 0.774817 \\ D2 & 0.591948 & 0.901514 & 0.865037 & 0.838193 & 0.851823 & 0.881752 \\ D3 & 0.733071 & 0.878968 & 0.892657 & 0.94071 & 0.904292 & 0.895728 \\ D4 & 0.893934 & 0.972274 & 0.899088 & 0.970249 & 0.898302 & 0.968244 \\ \hline \end{tabular}
\end{table} 
Table 2: The running time comparison results between DUNM and the other five algorithms. As Table 3, in the data table of task revenue comparison results corresponding to various algorithms, the first column indicates the data sets DI, D2, D3, and D4 and the increasing data sets from top to bottom. The second column indicates various algorithms under different stages of data sets, such as the DUNM algorithm, PS algorithm [45], DS algorithm [44], NS algorithm [46], Barrier algorithm [47], and Sifting algorithm [48] proposed in this study. The third and fifth columns indicate the metrics of the various algorithms at different stages of the dataset: the amount of successfully assigned tasks, the amount of unsuccessfully assigned tasks, and the total revenue, respectively. At different stages of the task dataset, our proposed algorithms successfully assigned all the scheduling tasks to the satellites, e.g., at dataset D1, all the tasks successfully assigned by our proposed algorithms amounted to 42, and the total revenue was 51.53; at dataset D2, the tasks successfully assigned amounted to 77, and the total revenue was 156.12; at dataset D3, the tasks successfully assigned amounted to is 102, generating a total revenue of 161.63; at data set D4, the number of successfully assigned tasks is 149, generating a \begin{table}
\begin{tabular}{c c c c} \hline
**Data Set** & **Algorithm** & **Task Successfully Assigned** & **Failed to Assign Task** & **Total Revenue** \\ \hline \multirow{8}{*}{D1} & DUNM & 42 & 0 & 51.53 \\  & PS & 40 & 2 & 38.52 \\  & DS & 40 & 2 & 38.52 \\  & NS & 40 & 2 & 38.52 \\  & Barrier & 40 & 2 & 38.52 \\  & Sifting & 40 & 2 & 38.52 \\  & DUNM & 77 & 0 & 156.12 \\  & PS & 65 & 12 & 82.7 \\  & DS & 65 & 12 & 82.7 \\  & NS & 65 & 12 & 82.7 \\  & Barrier & 65 & 12 & 82.7 \\  & Sifting & 65 & 12 & 82.7 \\  & DUNM & 102 & 0 & 161.63 \\  & PS & 46 & 56 & 125.7 \\ D3 & DS & 46 & 56 & 125.7 \\  & NS & 44 & 58 & 123.07 \\  & Barrier & 46 & 56 & 125.7 \\  & Sifting & 46 & 56 & 125.7 \\  & DUNM & 149 & 0 & 298.67 \\  & PS & 62 & 87 & 121.4 \\  & DS & 62 & 87 & 121.4 \\ D4 & NS & 62 & 87 & 121.4 \\  & Barrier & 63 & 86 & 121 \\  & Sifting & 61 & 88 & 120.95 \\ \hline \end{tabular}
\end{table} 
Table 3: Comparison of the total revenue of completing scheduling tasks between DUNM and the other five algorithms. Figure 9: Comparison of the algorithm’s running times for different data sets. total revenue of 298.67; all the remaining algorithms compared increase the number of unsuccessfully assigned tasks as the data set continues to increase, and even when the task data set is larger, the number of successfully assigned tasks is lower than the number of unsuccessfully assigned tasks; for example, the PS algorithm, at data set D1, the amount of successfully assigned tasks is 40, and the total revenue is 38.52; in data set D2, the amount of successfully assigned tasks is 65, and the total revenue is 82.7; in data set D3, the amount of successfully assigned tasks is 46, and the total revenue is 125.7; in data set D4, the amount of successfully assigned tasks is 62, and the total revenue is 121.4.