## 5 Performance Evaluation and Discussion
### Simulation Comparison of Single-Hop Proposed Model  
Figure 10 shows the lifetime graph of nodes concerning the passing periods (rounds). The same node deployment policy is adopted in the experiment. We can observe that the proposed technique shows a longer stability period than LEACH, LEACH-C, TEEN, TSEP, TDEEC, and HADCC protocols. The number of alive nodes in LEACH, LEACH-C, and TEEN declined quickly because of homogeneous nodes. TSEP, TDEEC, and HADCC show more enhanced performance because of multi-level energy nodes. HADCC has similar network attributes but proposed restrictions to reduce transmission helped to prolong the network lifetime. Our proposed model does not allow the network nodes to transmit packets when the same or minor change is observed from the system. This strategy in our proposed algorithm assists to prolong life as compared to the other popular approaches.  
Figure 11 shows the number of dead nodes as they run out of their limited energy. Our proposed model has more transmission time than LEACH, LEACH-C, TEEN, TSEP, and TDEEC protocols. The simulated results show that the networks with homogeneous nodes have low average energy and are wiped out too quickly. To prolong lifetime, nodes with advanced energy are used in TSEP, TDEEC, and HADCC. Smart deployment of nodes in HADCC and our scheme shows improved performance. As netw  
Figure 10: Number of alive nodes with respect to the network operational rounds.  
Figure 9: Number of packets sent by each sensor node with respect to the network operational rounds.  
and our scheme is the same but threshold-based controlled communication helps to prolong network stability.  
Next, we measure the number of cluster heads generated using various routing approaches that we use in our evaluation. In Figure 12, we ignored LEACH and LEACH-C to secure the space. The smallest energy drain helps to survive for a longer time. This stretched time period allows nodes to communicate and collect more information from the environment. We observe that our proposed algorithm shows enhanced performance because of the least consumption of restricted energy. This efficient use of energy leads to high network stability because of using the threshold technique for node placement in the WSN. This enhanced stability allows us to collect and communicate more information as compared to other protocols.  
Figure 11: Number of dead nodes with respect to the network operational rounds.  
Figure 12: Number of cluster heads generated per round.  
Figure 13 shows the performance of network stability with the proposed technique and compares it with the other popular algorithms that we have used in our evaluation. Moreover, Table 3 shows a comparison of our proposed model with other well-known clustering and routing approaches for performance metrics critical in WSNs. The random deployment of nodes may require unnecessary broadcasting to detect CHs at a wide range. So few nodes are wasting energy like other schemes. The introduction of controlled communication enhanced the lifetime of our scheme. Overall, we observe that our proposed model significantly outperforms the other approaches used in our evaluation.