# Adaptive Node Clustering Technique for Smart Ocean under Water Sensor Network (SOSNET)
## 4 SOSNET-Proposed Methodology
SOSNET generated only 18 clusters, whereas ACO created 28 clusters, CLPSO 34, and GWO created thirty-three clusters. When the transmission range was increased to 200 meters, SOSNET generated only two clusters in comparison to 3, 9, and 7 for ACO, CLPSO, and GWO, respectively. This is consistent with well-established studies showing that few numbers of clusters will be formed if the transmission range of the nodes are increased. Even when the transmission range was between 25 m and 200 m, SOSNET outperformed all the other algorithms and the results are evident from the figure. Similar kinds of results can be seen when the number of nodes was increased to 40, 80, 120, 160, and 200. This is shown in Figure 3b-e. By viewing the results, it is obvious that SOSNET outperformed all the other algorithms. It created the minimum number of clusters required to work in the given grid size. Figure 3: Grid size 500 m \(\times\) 500 m, nodes 40 to 200. ### Grid Size vs. Transmission Range vs. Number of Clusters

To make matters more concrete another set of experiments was carried out to check the performance of the proposed algorithm. In these experiments we varied the transmission range of the nodes from 50 m to 200 m while keeping the grid size static at 500 m \(\times\) 500 m and node density was taken as 200 nodes. The results of these experiments are shown in Figure 4. It is evident that even with the varied transmission range SOSNET performed equally well and in all instances gave the best results, whereas ACO was the closest one in these settings. Even with the grid size increased to 1 km \(\times\) 1 km SOSNET outperformed all the other algorithms. The results of this scenario are depicted in Figure 5. In this setting, when the node density was set at eightty nodes, SOSNET created 9 clusters. On the other hand, ACO created 13, CLPSO 19, and GWO 18 number of clusters. Clearly, SOSNET was providing a smaller number of clusters. When the node density was increased to 200, ACO created 9 clusters, GWO 19, and CLPSO created 24 clusters. On the contrary SOSNET created only six clusters, which showed that with this grid size, at any number of node density, SOSNET created a smaller number of clusters, thus optimizing the routing problem. It can also be seen that the transmission range had a direct impact on the number of clusters. This is consistent with other studies that show that more clusters are formed if the transmission range is low, since there tend to be fewer nodes in a cluster. If the range is increased, the nodes will find farther nodes as well, resulting in a fewer number of clusters. Figure 4: Grid size 500 m \(\times\) 500 m, transmission ranges 50 to 200. To further analyze the performance of SOSNET, the algorithm was experimented with different transmission ranges of the nodes while keeping the grid size and node density at a fixed value, i.e., 1 km \(\times\) 1 km and 200 nodes, respectively. The results, as shown in Figure 6, indicate that SOSNET was a perfect solution in the given situation and provided optimal results. Figure 5: Grid size 1000 m \(\times\) 1000 m, nodes 40 to 200. Simulations were also carried out while increasing the grid size to 1500 m \(\times\) 1500 m. The results of this setting are shown in Figure 2:0 It can be observed from Figure 6a that with lower transmission range all the algorithms except SOSNET provided similar results, whereas SOSNET provided optimal results, which shows the efficiency of the algorithm. It can also be observed that with the increasing number of nodes the performance of SOSNET also improved. For example, with the node density set to 200, SOSNET generated 9 clusters, whereas ACO was the second best with 14 clusters, GWO created 17 clusters, and CLPSO generated 21 clusters.