## 4 Performance Evaluation
### Simulation Result  
We compare the proposed ERG with AMSG as well as RTG, both of which are excellent energy-efficient algorithms based on geographic routing and have significant advantages in extending the lifetime of multi-hop networks. After that, we combine ERG with the DGS algorithm and NCS algorithm to improve the performance of the network comprehensively, so the final algorithm we propose is ERG-NCS. The following are the experiments we did, the average value of the simulation results is taken for 10 runs. The two main aspects of this paper are to improve the energy efficiency and data reliability of the network, the improvement of energy efficiency is reflected by the network lifetime and network energy consumption in the simulation results, the higher the network lifetime and the lower the energy consumption, the higher the energy efficiency of the network. As for the data reliability of the network, it is reflected by the packet delivery rate and the robustness of the network in the experiment; the higher the packet delivery rate and the better the network robustness, the more reliable the network is. Figure 8 exhibits the network PDR with a different number of sensor nodes. The ERG is able to detect and repair paths periodically, which greatly improves the reliability of the network, and thus the PDR of ERG is much higher than RTG and AMSG. On the other hand, RTG makes data collection less prone to produce holes due to the random mobility of nodes, and thus the PDR of RTG will be a bit higher than that of AMSG. Apart from that, the algorithms after considering the coverage are able to have more path selection options in data transmission because the nodes are less prone to die, thus the PDR of both \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline The Network size & 1000 m \(\times\) 1000 m \\ Number of nodes & 500–800 \\ Communication radius & 90 m–120 m \\ Coverage radius & 50 m \\ Data packet size & 50 bytes \\ Control packet size & 250 bits \\ Initial energy & 2 J \\ Coverage rate threshold & 0.9 \\ \(a\) & 250 m \\ \(\lambda\) & 0.5 \\ \(E_{dec}\) & 50 m/bit \\ \(\varepsilon_{fs}\) & 10 pJ/bit/m\({}^{2}\) \\ \(\varepsilon_{mp}\) & 0.0013 pJ/bit/m\({}^{4}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation parameters. NCS and DGS is a bit higher than the original algorithms, especially for NCS, as the nodes selected for work are the least number of nodes, the effect of such an increase is more obvious, and thus the PDR of ERG-NCS is the highest. Table 3 shows the PDR of these algorithms with different numbers of nodes, the underlined value is the highest PDR for each node number. The packet delivery rate of ERG is improved by 48.40% and 38.54% on average over the baseline algorithms AMSG and RTG, respectively, and this improvement is significant. After considering the node collaborative scheduling algorithms, the ERG-NCS algorithm is improved by 8.79% on average over the ERG, which is a good indication of the superiority of this network resource allocation. Figure 9 shows the network lifetime with different numbers of sensor nodes. Generally, as the number of nodes increases, the packets of the network increase, the energy consumption is accelerated and the network lifetime decreases. However, the considered coverage algorithms make full use of the network resources and generate packets by selecting only the nodes that satisfy the coverage rate threshold, so the considered coverage algorithms' lifetime is much larger than the original routing algorithms, and as the number of nodes increases the network's ready-to-work nodes also increase, so the network lifetime becomes longer. Although ERG has excellent PDR, it also leads to faster death of nodes in the inner area, so the network lifetime of ERG is a little lower. The autonomous mobile sink of AMSG is able to extend the lifetime of nodes around the sink, so the lifetime is a little higher than RTG. In considering the coverage algorithm, the network lifetime of ERG-DGS becomes quite longer.