## 4 AOS Elastic Slot Scheduling Strategy
For example, when the processing speed is \(0.5\times 10^{3}\) frames/s, EAMA reduces the delay by 67.6% compared to TAMA, and by 44% compared to FAMA under the stressed condition. This is because EAMA, by integrating channel scheduling status information, avoids the problems of unfair scheduling, slow response to sudden traffic changes, and large scheduling time jitter caused by the traditional algorithm, thus reducing the average VC scheduling delay. When the processing speed exceeds the network load, the delays for both EAMA and TAMA further decrease. This is because EAMA and TAMA predict the traffic volume and estimate the channel capacity during the scheduling period. When there is available capacity within the scheduling period, they reduce the frame generation algorithm's efficiency to lower the data delay. For asynchronous non-real-time traffic, it can be seen that the delays of all three algorithms are generally similar under both the normal condition and the stressed condition. However, EAMA has a slightly lower average delay due to its slot preemption capability. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Algorithm Name** & **Multiplexing Model** & **Synchronous Traffic** & **Asynchronous Real-Time Traffic** & **Asynchronous Non-Real-Time Traffic** \\ \hline Fixed-Time-Slot- & Packet Multiplexing Layer & Fixed Time Frame Generation Algorithm & Traffic-Prediction-Based Adaptive Frame Generation Algorithm & High-Efficiency Frame Generation Algorithm \\ \hline Multiplexing Algorithm (FAMA) & Virtual Channel Multiplexing Layer & Periodic Polling Scheduling Algorithm & Channel-State-Based Virtual Channel Scheduling Algorithm & Uniform Queue Length Virtual Channel Scheduling Algorithm \\ \cline{2-5}  & Decision Layer & Fixed Time Slot & Fixed Time Slot & Fixed Time Slot \\ \hline Elastic-Time-Slot- & Packet Multiplexing Layer & Fixed Time Frame Generation Algorithm & Traffic-Prediction-Based Adaptive Frame Generation Algorithm & High-Efficiency Frame Generation Algorithm \\ \cline{2-5}  & & & & \\ \cline{2-5}  & & & & \\ \cline{2-5}  & & & & \\ \cline{2-5}  & & & & \\ \hline Decision Layer & Fixed Time Slot & Fixed Time Slot & Fixed Time Slot \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Cont. ### Maximum Frame Remaining

The simulation results of the maximum frame remaining for three types of traffic under three algorithms are shown in Figure 4a-c.

As can be seen from the figure, for synchronous traffic, the maximum remaining frame quantity for the three algorithms is similar under both the normal condition and the stressed condition. This is because periodic messages account for a small proportion of

Figure 3: (**a**) Average scheduling delay of synchronous traffic; (**b**) Average scheduling delay of asynchronous real-time traffic; (**c**) Average scheduling delay of asynchronous non-real-time traffic. the network traffic, and their priority is relatively high under all conditions, resulting in a remaining frame quantity generally ranging from 1 to 5 frames. For asynchronous real-time traffic, it can be observed that when the processing speed is lower than the network load, EAMA effectively reduces the maximum remaining frame quantity, thereby lowering the demand for system buffering under both the normal condition and the stressed condition. For instance, when the processing speed

Figure 4: (**a**) Maximum frame remaining of synchronous traffic; (**b**) Maximum frame remaining of asynchronous real-time traffic; (**c**) Maximum frame remaining of asynchronous non-real-time traffic. is \(0.5\times 10^{3}\) frames/s, the maximum remaining frame quantity in EAMA is reduced by 49.6% compared to TAMA and by 22.7% compared to FAMA under the stressed condition. This is because EAMA incorporates the traffic prediction state information and slot preemption strategies, which provide stronger adaptability to dynamic network traffic changes, thus preventing certain virtual channels from being delayed in scheduling, thereby reducing the maximum remaining frame quantity.