# W-GUN: Whale Optimization for Energy and Delay-Centric Green Underwater Networks
## 4 Results and Discussion  
### Experimental Settings  
In this section, a brief description of the experimental settings is provided, which were used to set up Aqua-Sim-enabled network simulator (ns2) environments for evaluating the performance of the proposed underwater relay node optimization framework W-GUN. The underwater simulation environment had utilized acoustic channels at Medium Access Control (MAC) and physical layers. Towards benchmarking a centric comparative experimental analysis, recent techniques in underwater relay node optimization were considered, including VBF [27], HH-VBF [28], VBVA [29] and ES-VBF [35]. Both VBF and HH-VBF possess the qualities of service-oriented modeling without considering underwater network characteristics in the modeling. VBVA and VBF both focused on void avoidance without topology knowledge using the geographic locations of relay nodes. Here, the significant impact of underwater characteristics on relay node locations is not considered. The adapted optimization framework W-GUN for underwater relay node selection with a dynamic duty cycle is implemented under realistic 3D underwater network environments of size \(1000m\times 1000m\times 1000m\). Here, the underwater sensor nodes vary from 100 to 500 in the network region, which is quite a realistic assumption for scalability. Each sensor node in the region is charged with an initial energy of 100 j. For sending a single packet of size 512 bytes per node, the transmission energy per node is considered \(2w\), and receiving energy per node is considered to be \(0.75w\), given that the ideal node needs 10 mw of energy. The transmission range of each underwater sensor node is 150 m, and the movement of underwater nodes in the horizontal dimension is considered to be 0-3 m/s. There is the consideration of an 100 s beaconing gap in underwater networking communication. Due to the longer propagation delay in underwater networking environments, the handling packet collision is significant. The packets colliding in one node may not collide with other nodes or arrive in different sequential orders in underwater environments. This is handballed effectively in our Aqua-Sim-based simulations where every node maintains a local copy of incoming packets and collision of packets are identified using the difference in received power levels locally. Therefore, the effect of collision only remains on local copies of a node and does not impact the copies of other nodes. This is the way in which collisions are handled locally at each node in our simulation experiments. For controlling the constrains of underwater physical layer implementation, we are essentially setting the exposed interface values of the simulator. For example, as attenuation model setting, spreading factor was considered to be two, along with the absorption coefficient calculated following [PERSON]'s equation with 1500 m/s propagation speed. An average of 50 simulation runs are averaged to get the results, and overall simulation time considered to be 1500 s. A confidence interval of 98% was considered for generating the results. The framework is implemented in the C++ environment in the simulator.