# An Efficient Scalable Scheduling MAC Protocol for Underwater Sensor Networks +
## 6 Performance Evaluation
### Simulation Results  
The performance of ED-MAC is compared with those of UWAN-MAC and T-Lohi through simulations. For each scenario, the results are averaged over 50 runs, with a randomly generated topology in each run. The simulation results within two parameters studies the traffic effect and network scalability in every protocol and also shows how these three MAC protocols perform in practical underwater networks. In the first set of simulations, we compare the successful delivery ratio of all three protocols by varying offered traffic while the number of node equals to 10. Figure 11 shows the successful delivery ratio of each protocol as a function of offered traffic. The successful delivery ratio of ED-MAC outperforms that of other two MAC protocols, T-Lohi and UWAN-MAC. This is because ED-MAC has the ability to address the hidden node and the spatio-temporal uncertainty problems which cannot \begin{table}
\begin{tabular}{l l} \hline
**Parameter** & **Value** \\ \hline Transmission power & 2 Watts \\ Receiver power & 0.75 Watts \\ Idle power & 8 mW \\ Maximum transmission rage & 100 m \\ Bandwidth & 10 kb/s \\ Acoustic propagation speed & 1500 m/s \\ Offered traffic & 0.1–1.0 packet/s \\ Node Number & 10–100 sensor nodes \\ Deployment region & 10,000 m\({}^{2}\)\(\times\) 200 m \\  & 62,500 m\({}^{2}\)\(\times\) 500 m \\ Movement model & RandomWalk 2D mobility model \\ Movement speed of nodes & 2 m/s, change movement \\  & direction every 2 s \\ Running rounds & 50 \\ Control packet size & 100 bits \\ Data packet size & 2000 bits \\ Length of the initial phase & 30 s \\ Length of the scheduling phase & 30 s \\ Simulation time of one round & 3600 s \\ \hline \end{tabular}
\end{table} 
Table 2: Simulation parameters. be detected by UWAN-MAC protocol resulting in more packet loss and collisions. At a low traffic load, the successful delivery ratio of ED-MAC and T-Lohi almost achieves 100%, while UWAN-MAC only reaches 60%. This is due to the inefficient scheduling of UWAN-MAC, which causes considerably more collisions and retransmissions, where ED-MAC and T-Lohi exploit space-time uncertainty and high latency to avoid collisions and retransmissions. When the traffic is further increased, however, T-Lohi shows a fast degradation of the successful delivery ratio due to an increasing number of collisions of tone packets. The performance of ED-MAC in this simulation is far better than that of T-Lohi and UWAN-MAC, as ED-MAC employs a priority approach based on the depth of each sensor node to schedule the transmission and also to avoid data collisions. ED-MAC also allows more communications in one slot, by using temporal and spatial reuse, which significantly increases the acoustic channel utilisation for underwater networks. We then study the network scalability of each protocol by increasing the sensor nodes and keeping the offered traffic constant (with 0.25 packets/s). As can be seen from Figure 12, the successful delivery ratio of all three protocols is inversely proportional to the number of nodes. With 10 nodes, ED-MAC reaches 88% compared to 78% and 45% for T-Lohi and UWAN-MAC, respectively. This is due to the specific benefits of ED-MAC, such as high scalable scheduling; consequently, it can handle more packets than either T-Lohi or UWAN-MAC. When the number of nodes is increased, T-Lohi's successful delivery ratio rapidly reduces due to an increasing number of collisions of tone packets, thus resulting in incorrect reservations. The impact of increasing the number of nodes on the successful delivery ratio in T-Lohi is more profound. Still more interesting, however, is that UWAN-MAC only achieved 45% of the successful delivery ratio (within 10 nodes), which is much lower than the successful delivery ratio of either ED-MAC or T-Lohi. This is because UWAN-MAC is designed to only use one control packet across the network. Figure 11: Successful delivery ratio vs. offered traffic. Figure 12: Successful delivery ratio vs. node density.