# Self-Organized Proactive Routing Protocol for Non-Uniformly Deployed Underwater Networks
## 7 Computer Simulation Results  
Simulations were carried out using MATLAB(r) to estimate two efficiency parameters: the average delay from sending nodes to the gateway, and the average number of hops that each node employed to reach the gateway. The simulation parameters are given in Table 3.  
The average number of hops and delays were simulated for different weight combinations of RSS, number of hops, and number of neighbors. The starting weight was 0.2 and increased to 1 with steps of 0.2. The weight combinations used in the simulation are given in Table 4.  
Figure 11: Packet header format. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Value** & **Unit** \\ \hline Sound speed & 1500 & m/s \\ Data rate & 5000 & bits/s \\ Frequency & 48 & kHz \\ Header size & 30 & Bits \\ Transmission power & 18 & Watts \\ Nodes & 100 & nodes \\ Area & \(4\times 4\) & km\({}^{2}\) \\ Depth & 4 & km \\ Nodes density & 1.56 & nodes/km\({}^{3}\) \\ Number of runs & 100 & each \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulation parameters. The average number of hops for RSS weights 0.2 to 1 is shown in Figure 12. The graph shows that the average number of hops increased as RSS weight increased. This means that a node selects the forwarding node which closer to it, although it may have more nodes in the routing path to the gateway. The increase in the number of hops was approximately 34.83% as the RSS weight increased from 0.2 to 1 (6 versus 4.45 average hops). The average number of hops using weights between 0.2 to 1 is shown in Figure 13. The graph shows how that figure decreased as the weight increased. This means that a node prefers to select the forwarding node which needs a smaller number of hops to reach the gateway. In this case, the throughput increased due to the smaller number of hops to reach the gateway, although this may increase the average energy consumption per node. Also, the average number of hops became almost constant after 60% weight of hops. Comparison of the average number of hops to reach the gateway when the RSS weight was the maximum (the other two weights were zero) and when the number of hops weight was the maximum (the other two weights were zero) shows that the average number of hops decreased by more than 30% (6 versus 4.16 average hops). When the weight for least number of neighbors went from 0.2 to 1, the graph shown in Figure 14 was obtained. Like in case of RSS, the average number of hops increased as the weight for least number of neighbors increased. The analysis of packet delay from the node sending data to the gateway showed that it followed the same trend as the average number of hops, as can be observed in Figures 15-17. In the case of the least number of hops, the maximum weight decreased the delay by 12.2% compared to delay at weight = 0.2 (2.29 versus 2.61 min), 19.6% compared to delay at the maximum weight of RSS (2.29 versus 2.85 min), and 25.4% compared to delay at the maximum weight of least number of neighbors (2.29 versus 3.07 min). \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline  & & & & & & & & & & & & & & & & & \\ \hline RSS & 0.2 & 0.4 & 0.6 & 0.8 & 1 & 0.4 & 0.3 & 0.2 & 0.1 & 0 & 0.4 & 0.3 & 0.2 & 0.1 & 0 \\ Hops & 0.4 & 0.3 & 0.2 & 0.1 & 0 & 0.2 & 0.4 & 0.6 & 0.8 & 1 & 0.4 &The average energy consumption of a node to send a data packet was analyzed for multiple densities of the nodes. To compare with values given in RECRP [7] we assumed the same simulation parameters. The network area was 10 km \(\times\) 10 km \(\times\) 10 km and the number of nodes was 100, 200, 300, 400, 500, and 600. The data packet size was 256 bits and the transmission range was adjusted according to the node's density. The average energy consumption for multiple transmission range for each number of nodes was simulated as shown in Table 5. The simulation was run 10 times for each transmission range. Figure 16: Delay against hops weights. Figure 14: Number of hops against number of neighbors weights.