## 5 ESEDG Comparison with Existing Routing Protocol
### Performance Assessment  
To evaluate the proposed technique and to measure its performance, we selected the different appropriate benchmark studies Data Gathering Algorithm for Sensor (DSG), Data Gathering Algorithm for the AUV (DGA) [9], AUV-aided Energy-Efficient Data Collection (AEEDCO) and its variant Approximate AEEDCO-A [13], AUV-based location predictors (ALP) [23], and Scalable and Efficient Data Gathering (SEDG) [24]. The AUV-aided Efficient Data Gathering (AEDG) [21] is best suited for comparison. It is interesting to know that both these algorithms are used for data gathering purposes in the underwater environment. The data gathering classification method with layer swap mechanism is the core value of DSG-DGA. The DSG algorithm is designed for sensors that are the fundamental entity for the collection of data underwater, and DGA is used for the AUV with a purpose the same as DSG. The proposed and the compared approach have focused especially on end-to-end delay reduction. The other compared approach is the AUV-aided Energy-Efficient Data Collection (AEEDCO) and its variant Approximate AEEDCO-A [13]. It is a data collection protocol that is primarily based on the AUV working scenario. The selection of the AUV path is discussed in \begin{table}
\begin{tabular}{l l} \hline \hline
**Simulation Parameters** & **Values** \\ \hline Number of nodes & 350 \\ Network range & \(1200\times 1000\times 1000\) \\ Number of AUV & 1 \\ Number of sink nodes & 1 \\ Energy & Energy Model \\ Initial energy & 100 J \\ Acoustic network speed & 1500 m/s \\ Communication medium & Wireless \\ Wireless channel & Radio and Acoustic \\ Frequency & 15 KHz \\ Transmission range & 200 m \\ Receiving & 0.6 W \\ Data packet size & 50 B \\ Beacon message size & 54 B \\ Data rates & 12 kbps \\ Mobility & static and random \\ Transmission Power & 0.5 W \\ Idle Power & 0.008 W \\ Sleeping Power & 0.01 \\ Physical Layer & UnderwaterPhy \\ Mac Layer & UnderwaterMac \\ Antenna & OmniAntenna \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Simulation settings and their values. detail in the travel salesman problem. Our proposed approach is best described as a path in an elliptical shape and surrounded by a number of gateways with the same objective of reducing AUV traveling time. Another approach deemed fit for comparison is also the AUV AUV-location predictors (ALP) [23]. This is a data collection scheme to balance the energy consumption in an underwater wireless sensor network. ALP works for the AUV trajectory by sending and receiving data from the AUV to sink and vice versa. The trajectory of the AUV in ALP and the elliptical shape in the proposed approach are the same and provide enough time for receiving and sending data through the AUV directory. Therefore, ALP is considered to prolong the network lifetime and PDR more than the other AUV-based approaches. The justification of these approaches is just AUV-based mechanism and data collection scheme. The Scalable and Efficient Data Gathering (SEDG) [24] routing protocol with the number of associated Gateways Nodes (GNs) and its selection criteria based on RSSI and Shortest Path Tree (SPT) is restricted to energy efficient. The movement of the AUV underwater is elliptical. Therefore, GNs are dependent according to the quantity of Member Nodes (MNs). The well-known and considered baseline approach in this work includes using the AUV as a central focus for data gathering. The AUV-aided Efficient Data Gathering (AEDG) [21] routing protocol for reliable data delivery is used. In our proposed scenario, we compare AEDG with ESEDG and evaluate path and transmission loss (both are measured in dB), average end-to-end delay, PDR, number of dead nodes, network throughput, and network lifetime, respectively. For evaluation, the experimental setup includes from 50 nodes to 350 with a 3D environmental area of \(1200\times 1000\times 1000\) m\({}^{3}\). The initial energy is 100 J, which can increase or decrease during simulation with increments in the transmission range.