# An On-Demand Scheduling-Based MAC Protocol for UW-WiFi Networks
## 5 Experiments and Results
### Ocean Field Trials Implementation
It is apparent that the network throughput gradually rises and finally stabilizes with the increase in the number of data packets sent, which conforms with the throughput simulation results. However, through Figure 10, we can obtain that the field trial results are slightly lower than the simulation results. This is because the underwater acoustic communication link is unstable due to the serious ocean conditions during the trial, resulting in a high bit error rate, which causes packet decoding failures and being dropped. Figures 11 and 12 depict the simulation and sea test consequences of channel utilization and end-to-end delay on the proposed SDDA scheme, respectively. As the packet generation rate rises, it results in an increase in the number of data packets, thereby significantly increasing the time that the data occupy the channel and the data queueing delay in each round of transmission. Hence, the channel utilization and end-to-end delay increase as  
Figure 9: Packet delivery ratio comparison. illustrated in Figures 11 and 12. From Figure 11, we can also see that the channel utilization eventually converges to a certain value. This is because the maximum number of packets sent by each node each time is fixed, and when the number of packets sent reaches the maximum, the channel utilization will no longer increase. The field experiment results are in line with the simulations on both of the two performances. When the number of packets sent is unlimited and tends to infinity (i.e., the packet generation rate tends to infinity), the channel utilization will be infinitely close to 100%, but the end-to-end delay will become considerable. Therefore, in practical applications, we should consider a trade-off between the two performances to choose the most appropriate packet generation rate based on the application requirements. Figure 11: Channel utilization. Figure 10: Network throughput. Figure 13 presents the simulation and sea field experiment results of the packet delivery ratio of the SDDA mechanism. From Figure 13, we can observe that the packet delivery ratio holds steady at around 90%, and even reaches 100% once in a while. Compared to the results of the simulation, those of real sea tests are a little lower in Figure 13. For the reason that underwater acoustic communication suffers from intermittent connectivity in consequence of harsh hydrological environment varying with time in real sea trials, which brings about erratic packet loss. Though, thanks to the mechanism of acknowledgment and retransmission in the SDDA protocol, the network has a low packet drop ratio. Figure 12: End-to-end delay. Figure 13: Packet delivery ratio. Experiment II:  
Figure 14 illustrates the data of various sizes from terminal nodes at different ranges. These test results from the real scenario, as demonstrated in Figure 14, indicate that the proposed protocol effectively addresses the issue of diverse data needs of different functional nodes in real-world ocean applications by the on-demand scheduling scheme. Additionally, the trial also manifests that terminal nodes at different distances have an equal opportunity to send data in each transmission round. Thus, there will not be a situation where the short-range nodes frequently pre-empt the channel, resulting in the data backlog of long-range nodes. Therefore, the SDDA protocol achieves good fairness amongst terminal nodes. Apart from that, this protocol reduces energy usage to prolong the network lifetime by using fewer control packets and the conflict-free scheduling.