## 5 Simulation and Performance Analysis
### Simulation Example
#### 5.2.2 Effect of Varying \(N\) on Every Indicator  
Figure 12 presents the comparison of the network coverage rate with varying numbers of nodes. The figure shows that the network coverage rates of both URSA and CDA increase, but the trend gradually slows down with the increasing number of nodes. The network coverage rate of URSA is always higher than that of CDA with the same number of nodes, because CDA only considers the \(CRR\) on the position where the distance between the node and each of its basic nodes is \(R_{c}\) and does not consider the situation of the other positions where the distance between them is less than \(R_{c}\). In the situation that CDA does not consider, a node may overlap in such a position. However, the total \(CRR\) rate of the node may be less than that in the situation that CDA can consider. In URSA, the process of node adjusting depth considers the aforementioned limitation, compares the \(CRR\) of all possible positions and selects the best position. Therefore, under the circumstances of losing some network coverage rate because of improving the network reliability, the network coverage rate of URSA remains higher than that of CDA. Figure 13 illustrates the comparison of the number of nodes within the \(R_{c}\) range of the sink node for the varying numbers of nodes. In the figure, the number of nodes within the \(R_{c}\) range of the sink node generally increases in both of the two algorithms. However, compared to CDA, URSA shows improved results with the same number of nodes. URSA uses the uneven clustering process to form a layout in which the number of cluster head nodes in an area close to the sink node increases, whereas  
Figure 11: Network reliability of URSA for varying _rang_. Figure 12: Comparison of network coverage rate for varying numbers of nodes. CDA, CDS-based depth computation algorithm. the size of the cluster in that area decreases. URSA adjusts the position of the cluster head nodes according to the principle of maintaining this layout to increase the number of cluster head nodes near the sink node. The size of the cluster in the area close to the sink node becomes small, and all in-cluster nodes adjust their depth by minimizing their hop number, thereby increasing the chance for in-cluster nodes close to the sink node to some extent. Figure 14 shows the comparison of the average number of neighbor nodes for a varying number of nodes. The figure shows that the average number of neighbor nodes of the two algorithms increases with increasing the number of nodes. The number of URSA is always smaller than the number of CDA, but the difference between URSA and CDA becomes insignificant gradually with the increasing number of nodes. Figures 13 and 14 indicate that compared to CDA, the average number of neighbor nodes of URSA is low. Nevertheless, the number of nodes within the \(R_{c}\) range of the sink node of URSA is obviously higher than that of CDA, thus maintaining the good performance of the network during its operation after being deployed. The network energy consumption includes the energy consumption of network deployment and the energy consumption of network operation. According to [40], the energy consumption of a moving node is significantly greater than the energy consumption of the communication among nodes during node deployment. Thus, this study only regards the energy consumption generated by nodes adjusting their depth as the energy consumption of network deployment. For the energy consumption of network operation, its value is usually related to the routing algorithm or protocol that the network used when it operates. However, when the number of nodes is relatively sparse, the problem of the energy consumption of the network operation is related to the topology formed by  
Figure 14: Comparison of the average number of neighbor nodes for a varying number of nodes. Figure 13: Comparison of the node number within the \(R_{c}\) range of the sink node for a varying number of nodes.