## 5 Simulation Results and Performance Analyses
### Performance Evaluation of \(CLCQ\)
This  
Figure 10: Residual energy variance under different \(\varphi_{en1}\) and \(\varphi_{en2}\) values. Figure 9: Total energy consumption under different \(\varphi_{en1}\) and \(\varphi_{en2}\) values. approach helps to achieve a balanced distribution of energy, thereby reducing the residual energy variance. On the other hand, when \(\varphi_{cn1}\) increases, the network is inclined to select nodes with a considerable residual energy, which also serves to diminish the residual energy variance. Consequently, the residual energy variance of nodes gradually tends to become balanced over time following multiple packet transmissions. In conclusion, by modifying the values of \(\varphi_{cn1}\) and \(\varphi_{cn2}\), a trade-off between network energy consumption and residual energy balance can be achieved. While increasing these two parameters can reduce the variance of residual energy and promote the balanced distribution of energy, it will also increase the total energy consumption of the network. Consequently, in practical applications, it is necessary to select reasonable values for these two parameters based on the specific needs and objectives of the network to achieve optimal network performance. Figure 11 illustrates the impact of varying \(\varphi_{t}\), \(\alpha_{1}\), and \(\alpha_{2}\) on the average end-to-end delay when 100 nodes are deployed in the network. Under the configuration of \(\varphi_{t}=1\), \(\alpha_{1}=0.9\), \(\alpha_{2}=0.1\), the average end-to-end delay is 76.78 s. In contrast, when \(\varphi_{t}=0.1\), \(\alpha_{1}=0.1\), and \(\alpha_{2}=0.9\), the average end-to-end delay is 85.78 s, which is approximately 9 s shorter than that of the latter. The results illustrate that, by adjusting the values of \(\varphi_{t}\), \(\alpha_{1}\), and \(\alpha_{2}\), the network delay can be effectively reduced and the network performance can be optimized. Firstly, an increase in the value of \(\varphi_{t}\) makes the protocol more inclined to select those nodes with a lower latency when choosing the next hop node, and consciously avoid the congestion area. This is because the time required for multiple retransmissions caused by congestion is considerably longer than the time required for a successful single transmission, indicating that congestion has a more significant impact on the network. Furthermore, while maintaining \(\varphi_{t}\) constantly, increasing \(\alpha_{1}\) can more effectively avoid severely congested neighboring nodes. This strategy facilitates a reduction in the number of packets that must traverse the congested area, thereby reducing the average end-to-end delay of the entire network. Figure 12 illustrates the impact of varying \(\varphi_{q}\) and \(\varphi_{t}\) values on PDR when 60 nodes are deployed in the network. Firstly, an increase in \(\varphi_{q}\) means that the protocol is more inclined to select nodes with a lower bit error rate as the next hop. A reduction in the bit error rate will lead to an improvement in link quality and reliability, resulting in fewer errors and retransmissions during data transmission. This significantly enhances the PDR. On the other hand, increasing \(\varphi_{t}\) tends to cause the protocol to avoid nodes that lead to multiple retransmissions due to congestion, which also increases the PDR. Although congestion management is equally important for improving the PDR, the impact of channel  
Figure 11: Average end-to-end delay under different \(\varphi_{t}\), \(\alpha_{1}\), and \(\alpha_{2}\) values. quality on the PDR seems to be more significant, as illustrated in Figure 12. When \(\varphi_{t}=0.1\), as \(\varphi_{q}\) increases, the PDR increases more rapidly than when \(\varphi_{t}=0.9\). This indicates that channel quality is a more significant factor in this protocol, and its impact on PDR is more pronounced than that of congestion. Therefore, it is necessary to consider both the channel quality of physical layer and the congestion degree of the link layer in cross-layer design.