## 4 Experiments and Results
Thus, they are attaining maximum routing delays of 230 ms and 240 ms, respectively. Similarly, the performance is not optimal for link recreation phase as provided in Table 5.  
Figure 11 and Table 6 illustrate closely related performance metrics such as secure throughput achievement rate and retransmission reduction rate for each channel. Nevertheless, secure throughput rate shows the amount of successful data transmission against malicious interruptions. The secure throughput of each channel is ensured and obtained with VGAN-IDS engine installed in each sensor node. In this experiment, the proposed DMCAP achieves secure throughput from 17.2 Kilobits Per Seconds (Kbps) to 23.9 Kbps when the number of training epochs are increasing gradually. Moreover, the throughput of CRLR obtains better states compared with OETN and SMC. OETN and SMC maintain only nominal security against malicious event (15.6 Kbps and 13.1 Kbps). This experiment reveals that the proposed technique securely manages the data transmission under VGAN-IDS initiatives and alert systems. Due to the immense experiment-based observations, the number of retransmissions initiated at each link is crucially reduced in WUGSN (DMCAP). Figure 10: Average routing delay. Table 6 shows the observed results for the DMCAP system's retransmission reduction rate. The rate of retransmission is reduced as the number of epochs increases. The retransmission reduction rate is defined as the number of retransmissions required at each sensor node against environmental interrupts and malicious interrupts on the link. As illustrated in Table 6, the proposed system reduces the retransmission rate (%) from 90.1% to 99.5% successfully. This indicates that the energy and lifetime of each sensor node on the link is saved with the benefit of proposed DMCAP procedures. As per the theoretical and experimental clarifications, the proposed system was implemented as distributed multi-channel assessment and activation protocol in each sensor node. The proposed DMCAP is a light-weight protocol installed in both underground and surface sensor nodes for ensuring reliable data communication under uncertain WUGSN conditions. This protocol is fast and reactive in the uncertain channel environment. Particularly, DMCAP uses ensemble multi-channel attribute assessment procedures (ENLSVM) and VGAN-IDS engines as sensor internal procedures. Thus, the proposed DMCAP overcomes data communication problems that happen due to nonlinear productions and channel uncertainty issues optimally compared with other techniques (SMC, CRLR, and OETN). Notably, the proposed model effectively detects and predicts the channel attributes for managing the quality of wireless communication. The contributions and advantages of \begin{table}
\begin{tabular}{c c} \hline \hline
**e(r)** & **DMCAP** \\ \hline
20 & 90.1 \\
40 & 96.7 \\
60 & 97.3 \\
80 & 97.9 \\
100 & 98.9 \\
120 & 99.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Retransmission reduction rate (%). Figure 11: Secure throughput rate. the proposed DMCAP model was illustrated through various testbed experiments against channel uncertainties. To achieve significant benefits from proposed channel assessment policies, the testbed was configured with dual-link characteristics to meet the conditions of underground channel assumptions and surface level channel assumptions. The configuration of classified channel configuration parameters helps to observe the crucial and real-time performance of proposed DMCAP model (Tables 2 and 3). However, these dual-link configuration properties are not used in existing techniques. On the realistic testbed, experiments are taken to illustrate the real-time uncertainty conditions of WUGSN using the measured quantities of noise distortion rate, retransmission rate, channel interference rate, data rate, and other uncertainties (link and node failures). Figures 5 and 6 infer the dynamic nature of the WUGSN setup.