# Adaptive Node Clustering Technique for Smart Ocean under Water Sensor Network (SOSNET)
## 4 SOSNET-Proposed Methodology
As with the previous two scenarios, SOSNET was again evaluated with the varied transmission range from 50 m to 200 m and keeping the grid size at 1500 m \(\times\) 1500 m. The results are depicted in Figure 2:1 It is interesting to note that there was a huge performance difference between SOSNET and the other algorithms when the transmission range of the nodes was set to 200 m in the given setting. This shows that with the increasing transmission range the performance of SOSNET improved further and it created very few numbers of clusters. Figure 2:2 Grid size 1000 m \(\times\) 1000 m, transmission ranges 50 to 200. Figure 2:3 Grid size 1500 m \(\times\) 1500 m, nodes 40 to 200. Similar kinds of results were observed when the grid size was enhanced to 2 km \(\times\) 2 km. The results of this grid size are shown in Figure 2:4 In this setting, with the transmission range set to 100 m and node density set at 160 nodes, both CLPSO and GWO performed poorly, creating 27 and 22 clusters, respectively, whereas ACO created 13 clusters. However, SOSNET performed excellently by generating only nine clusters. In the extreme situation where transmission range was considered as 200 m and node density was set to 200, SOSNET generated 11 clusters, whereas the closest one, i.e., ACO, generated 16 clusters. The same results were observed when various parameters were changed, such as grid size, transmission range, and number of nodes. This proves that SOSNET was the best solution and provided the optimal number of clusters in any given setting. The same results were also observed with the transmission range set to 50, 100, 150, and 200 m while keeping other settings constant at 200 nodes and 2 km \(\times\) 2 km. It can be clearly observed from Figure 10 that SOSNET's performance was best among these protocols. This shows that SOSNET gave the best results in any given scenario. Figure 2:5 Grid size 1500 m \(\times\)1500 m, transmission ranges 50 to 200. Figure 2:6 Grid size 2000 m \(\times\) 2000 m, nodes 40 to 200. In order to evaluate SOSNET in a more realistic real-world scenario, a final set of simulations was also run on a 3D grid with a transmission range of 50 m to 200 m and a grid size of 500 m \(\times\) 2000 m with the node density set to 40 and 80 nodes. The results are depicted in Figure 2:7 It shows that even in this scenario, SOSNET performed better than the other algorithms. Figure 2:8 _Cont._

Figure 2:9 Grid size 2000 m \(\times\) 2000 m, transmission ranges 50 to 200. ### Load Balance Factor

As mentioned above, it is not possible to have an equal number of nodes in each cluster. It is important to calculate the load on each CH. LBF is also calculated for each CH by following Equation (5):

\[\text{Delta}_{\text{Diff}}=\text{ABS}\;(\text{Ideal}_{\text{Degree}}-\text{ Node}_{\text{Degree}}). \tag{2}\]0

where \(n_{c}\) is the number of clusters, \(x_{i}\) is the cluster's cardinality, and \(-u\) is the average number of neighbors of a CH. Figure 12 shows the LBF calculated for a grid size of 1000 m \(\times\) 1000 m; the transmission range is taken from 25 m and the node density ranges from 20 to 200 nodes. It can be observed that SOSNET performed well when the neighbors' numbers reached the threshold value in terms of load balancing in the network. By looking at Figure 12, some general observations can be made. When the transmission range was increased, a fewer number of clusters were formed. This implies that the number of clusters is inversely proportional to the transmission range. On the other hand, an increase in grid size resulted in a higher number of clusters, effectively showing that both these were proportional to each other. Another observation can be made while observing the distance between nodes and grid size. The distance between the nodes and grid size were directly proportional to each other. The above discussion and results prove that SOSNET provides optimal result in UWSN and make it a promising candidate of routing algorithms in this scenario.