# Investigating Master-Slave Architecture for Underwater Wireless Sensor Network
## 4 System Model
### Restricting Extra Reception of Packets:
In contrast to WDFAD, fix the amount of transmission energy is used for packets transmission on each hop irrespective of the next forwarder displacement. In the sparse environment, this approach does not play a major role in saving energy due to the wide dispersion of the nodes in the specified range. However, in a dense network, there is a mighty part played by this approach because a greater number of nodes is present in the maximum range. In general, trend (most rare), the source node must transmit with the maximum power so that it targets maximum numbers of the nodes in its proximity. Though, in WDFAD, the source node will transmit with the maximum fixed power even its next forwarder is closer to it. The process of adaptive transmission power leveling significantly reduces energy consumption without affecting any other performance metric. Therefore, either the sparse or the dense, the novel protocol (ERPMSA-UWSN) persuasively outperformed the competing protocol (WDFAD) in terms of energy usage. End-to-end delay is associated with the average time taken by a packet to reach its destination. This average time includes transmission time, processing time, idle state time, and propagation time. Propagation time and processing time matter in delay-tolerant protocols, for instance, the presented protocol in which propagation time and the processing time are extended due to the distance-based calculation of the holding time and activation time. In contrast, the holding time calculation of WDFAD is based on the weighting depth of the nodes, which results in a minimal end-to-end delay. The E2 ED is directly associated with the behavior of the APD curve. The APD of the presented protocol is higher than the competing protocol because of the longer route followed by the packet, in search of the best forwarder in the network. Our protocol keep account of whether the packet reached the destination successfully, irrespective of the length of the route. On the other hand, WDFAD keeps the track of the route followed by the packet, which leads to low APD. We recorded the percentage improvement in the PDR and energy tax, as listed in Table 4.

#### 5.3.2 Simulation Results Based on Sink Variation

To investigate the best economical options, we analyzed our protocol's performance with the standard number of sinks (7) as well as a higher number (9) used by the existing \begin{table}
\begin{tabular}{c c c} \hline \hline
**Number of Nodes** & **\% Improvement in PDR** & **\% Improvement in Energy Tax** \\ \hline
100 & 26 & 47 \\
150 & 9 & 43 \\
200 & 2 & 6 \\
250 & 1 & 2 \\
300 & 1.5 & 3 \\
350 & 1.4 & 4.1 \\
400 & 1.1 & 3.5 \\
450 & 0.98 & 4.2 \\
500 & 0.9 & 4.6 \\ Total Avg & 4.8 & 13 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Qualitative analysis of the ERPMSA-UWSN based on PDR and energy tax with WDFAD. WDFAD-DBR. Our proposed protocol does not perform well for 7 sinks as compared to 9 sinks, in both sparse and dense networks. This behavior is obvious as by decreasing the number of receivers in a network reduces the network's performance. Consequently, the load on a single receiver increases which results in the increase of packets collision. Furthermore, this results in a lower PDR, higher energy tax, E2 ED, and a higher APD, as shown in Figure 14a-d, respectively. Another limitation is the slow growth noted in a dense network. It is because ERPMSA-UWSN has limited sources of data packets after suppressing the majority of the PFNs, in contrast to WDFAD. The possibility of a void/energy hole and/or the absence of the potential forwarding node in the transmission range still exists. ## 6 Conclusions and Future Work

In this paper, we proposed a novel protocol, called Efficient Routing Protocol based on Master-Slave Architecture for Underwater Wireless Sensor Network (ERPMSA-UWSN) that aims to optimize energy consumption in the network. The routing scheme of ERPMSA-UWSN is based on several parameters including the neighboring nodes, hops count, energy level, master selection function, and holding time.