# Energy-Efficient Opportunistic Routing Algorithm for Post-Disaster Mine Internet of Things Networks
## 5 Performance Evaluation
### Performance for Varying Number of Nodes  
In this section, we evaluate the network performance of the DEOR algorithm by varying the number of nodes from 200 to 300. In the simulation, the control parameter is set to \(\alpha_{\theta}=\alpha_{d}=1\), \(\alpha_{\varepsilon}=5\), and the communication range is set to 40 m. Other parameters for this simulation are listed in Table 3. The results can be found in Figures 13-16. Figure 13: Energy consumption varying with number of nodes. Figure 13 illustrates the influence of the number of nodes on the energy consumption. It is clearly seen that as the number of nodes becomes larger, the energy consumption of all four routing algorithms increases. This is because when the size of the monitoring area is fixed, more nodes in the network imply a higher network density, and then the number of nodes involved in forwarding increases. Excessive forwarding nodes will generate more redundant packets in the network, which in turn leads to higher energy consumption. Figure 16: Network lifetime varying with number of nodes. Figure 14: Average number of hops varying with number of nodes. Figure 15: Packet delivery ratio varying with number of nodes. DEOR has the smallest increase in energy consumption among the four algorithms because the number of forwarders in DEOR is controlled by the network density \(D\). According to Formula (4), when the network density \(D\) increases, the width \(w_{i}\) of the forwarding area will decrease, thereby limiting the number of nodes in the CFS. However, for the ORR, OBRN, and ECSOR algorithms, as the number of nodes in the network increases, the number of nodes participating in forwarding will also increase, generating more redundant packets and, therefore, leading to more energy consumption. Figure 14 illustrates the influence of the number of nodes on the average hop count of delivered packets. It is observed that the average hop count in all four algorithms gradually decreases as the deployment density of nodes increases. This is because when the communication radius \(r\) of nodes is fixed, the number of nodes in the network is small, leading to a sparse local topology, and packets need to pass through a large number of relay nodes to enter the coverage range of the sink. Therefore, the average number of hops for packet forwarding is higher. On the contrary, when the number of nodes is higher, there are fewer void nodes, and packets are theoretically able to enter the coverage of the sink through the shortest path, resulting in a lower average number of hops. Compared with ORR, OBRN, and ECSOR, DEOR has the fewest number of hops. According to Formula (23), DEOR updates the transmission distance metric in the routing decision. DEOR selects optimal relay nodes closer to the void node by adopting a recovery mechanism, thereby shortening the length of the communication link. Figure 15 illustrates the influence of the number of nodes on the packet delivery ratio. Obviously, the PDR of all four algorithms gradually increases as the number of nodes becomes larger. When the deployment density of nodes is higher, the probability of routing void areas decreases, and there are more available candidate nodes for packet forwarding. As a result, the probability of packet loss is reduced, and the packet delivery success rate is improved. ORR has the lowest PDR among the four routing algorithms. This is because only the residual energy of nodes is considered in ORR. If there are fewer nodes in the network, it is prone to a large amount of packet loss. Additionally, as shown in Figure 15, when the number of nodes approaches 300, the PDR of OBRN, ECSOR, and DEOR algorithms are close to the same, approximately 90%. However, when the number of nodes is less than 300, the DEOR algorithm is significantly better than OBRN and ECSOR. This is because when a sparse topology appears in the network, DEOR can increase the number of forwarders, thereby improving the reliability of successful packet forwarding.