## 4 AOS Elastic Slot Scheduling Strategy
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Algorithm Name**} & \multirow{2}{*}{**Multiplexing Model Layer**} & \multirow{2}{*}{**Synchronous Traffic**} & \multicolumn{2}{c}{**Asynchronous**} & \multicolumn{2}{c}{**Asynchronous**} \\  & & **Layer** & & **Real-Time Traffic** & **Non-Real-Time Traffic** \\ \hline \multirow{4}{*}{Traditional AOS Multiplexing Algorithm (TAMA)} & Packet Multiplexing Layer & Fixed Time Frame Generation Algorithm & Adaptive Frame Generation Algorithm & Adaptive Frame Generation Algorithm \\ \cline{2-6}  & \multirow{2}{*}{Virtual Channel Multiplexing Layer} & Periodic Polling Scheduling Algorithm & Dynamic Priority Scheduling Algorithm & Dynamic Priority Scheduling Algorithm \\ \cline{2-6}  & & Decision Layer & Fixed Time Slot & Fixed Time Slot & Fixed Time Slot \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation algorithm configuration. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Virtual Channel**} & \multirow{2}{*}{**Traffic Type**} & \multirow{2}{*}{\begin{tabular}{c} **Data** \\ **Source** \\ **Name** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Average** \\ **Data** \\ **Arvival** \\ **Rate (Mb/s)** \\ \end{tabular} } & \multicolumn{2}{c}{**Normal Condition**} & \multicolumn{2}{c}{**Stressed Condition**} \\ \cline{3-8}  & & & **Data** & **Traffic Distribution** & **Traffic Distribution** & **Traffic Distribution** & **Traffic Distribution** \\ \hline \multirow{2}{*}{VC 1} & Synchronous Traffic & Real-time & & Uniform & \multirow{2}{*}{\begin{tabular}{c} 3.33 \(\times\) 10\({}^{-5}\) \\ Distribution \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} Poisson \\ Distribution \\ \end{tabular} } & \multirow{2}{*}{0.04} \\  & & & & & & & \\ \hline \multirow{2}{*}{VC 2} & Synchronous Traffic & Command & & Uniform & \multirow{2}{*}{\begin{tabular}{c} 8.33 \(\times\) 10\({}^{-6}\) \\ Distribution \\ \end{tabular} } & \multirow{2}{*}{0.01} \\  & & & & & & & \\ \hline \multirow{2}{*}{VC3} & Synchronous Traffic & Network Management & & Uniform & \multirow{2}{*}{\
\begin{tabular}{c} 8.33 \(\times\) 10\({}^{-6}\) \\ Distribution \\ \end{tabular} } & \multirow{2}{*}{0.01} \\  & & & & & & & \\ \hline \multirow{2}{*}{VC4} & Asynchronous Real-time Traffic & & & & & & \\ \hline \multirow{2}{*}{VC5} & Asynchronous & & & & & & \\ \hline \multirow{2}{*}{VC6} & Asynchronous & & & & & & \\ \hline \multirow{2}{*}{VC7} & Real-time Traffic & & & & & & \\ \hline \multirow{2}{*}{VC7} & Asynchronous & & & & & & \\ \hline \multirow{2}{*}{VC8} & Asynchronous & & & & & & \\ \hline \multirow{2}{*}{VC9} & Real-time Traffic & & & & & & \\ \hline \multirow{2}{*}{VC9} & Asynchronous & & & & & \\ \hline \multirow{2}{*}{VC10} & Asynchronous & & & & & & \\ \hline \multirow{2}{*}{
\begin{tabular}{c} Asynchronous \\ Non-real-time \\ Traffic \\ \end{tabular} } & Synchronous Traffic & & & & & & & \\ \hline \multirow{2}{*}{VC10} & Asynchronous & & & & & \\ \hline \end{tabular}
\end{table} 
Table 1: Simulation data source settings. ### Average Scheduling Delay

The simulation results of average scheduling delay for three types of traffic under three algorithms are shown in Figure 3a-c.

As can be seen from the figure, for synchronous traffic, EAMA exhibits the lowest delay under both the normal condition and the stressed condition. This is because TAMA and FAMA lack a slot preemption mechanism. When periodic messages arrive and no slot is available, they must wait for the next available slot. In contrast, EAMA can reduce the delay of critical periodic messages by preemptively acquiring scheduling slots when periodic messages arrive, thus lowering the delay. For asynchronous real-time traffic, it can be observed that when the processing speed is lower than the network load, EAMA shows a significant performance advantage under both the normal condition and the stressed condition.