## 4 Performance Validation
From the figure, it is portrayed that the PSOA and MOPSOA models have demonstrated least throughput over the other methods. Meantime, GOA and GSOA models have exhibited even better throughput, but not superior to GEER-DLAD model. However, the GEER-DLAD model has depicted improved throughput across the related methods. For instance, on the applied 10 IoT devices, the GEER-DLAD model has attained a higher throughput of 0.95 Mbps while the GSOA, GOA, MOPSOA, and PSOA models have exhibited reduced throughput of 0.92 Mbps, 0.91 Mbps, 0.89 Mbps, \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**No. of IoT**} & \multicolumn{5}{c}{**Network Lifetime (Rounds)**} \\ \cline{2-6}  & **GEER-DLAD** & **GSOA** & **GOA** & **MOPSOA** & **PSOA** \\ \hline
10 & 5600 & 5500 & 5200 & 4800 & 4500 \\ \hline
20 & 5500 & 5300 & 5000 & 4500 & 4300 \\ \hline
30 & 5300 & 5000 & 4800 & 4300 & 4200 \\ \hline
40 & 5100 & 4900 & 4700 & 4200 & 3800 \\ \hline
50 & 4900 & 4700 & 4500 & 4000 & 3600 \\ \hline
60 & 4600 & 4300 & 4200 & 3700 & 3500 \\ \hline
70 & 4400 & 4100 & 3900 & 3400 & 3300 \\ \hline
80 & 4100 & 3800 & 3500 & 3300 & 3200 \\ \hline
90 & 3900 & 3500 & 3300 & 3000 & 2900 \\ \hline
100 & 3800 & 3300 & 3100 & 2900 & 2800 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The Result Analysis of Existing with Proposed GEER-DLAD Method in terms of Network Lifetime (Rounds). Figure 5: The Energy consumption analysis of GEER-DLAD model. and 0.85 Mbps. Followed by, on the applied 50 IoT devices, the GEER-DLAD model has obtained a maximum throughput of 0.84 Mbps whereas the GSOA, GOA, MOPSOA, and PSOA models have illustrated minimal throughput of 0.67 Mbps, 0.60 Mbps, 0.55 Mbps, and 0.47 Mbps iterations. Similarly, on the applied 100 IoT devices, the GEER-DLAD model has accomplished maximum throughput of 0.70 Mbps whereas the GSOA, GOA, MOPSOA, and PSOA models have implied reduced throughput of 0.56 Mbps, 0.48 Mbps, 0.47 Mbps, and 0.38 Mbps. Figure 6: The Network lifetime analysis of GEER-DLAD model. Figure 7: Throughput analysis of GEER-DLAD model. Table 4 and Figure 8 examines the average delay results of the GEER-DLAD with existing methods with respect to distinct IoT devices. The resultant figure reported that the PSOA technique has resulted in poor performance by exhibited higher average delay. Followed by, the MOPSOA has revealed slightly reduced average delay over PSOA. At the same time, the GSOA and GOA models have depicted closer average delay. However the presented GEER-DLAD model has accomplished better performance by gaining reduced average delay over all the other compared methods. For example, on the applied 10 IoT devices, the GEER-DLAD model has exploited a minimum average delay of 2.02 s and the GSOA, GOA, MOPSOA, and PSOA models have depicted higher average delay of 2.22 s, 2.32 s, 2.34 s, and 2.97 s correspondingly. At the same time, on the applied 50 IoT devices, the GEER-DLAD model has exploited a minimum average delay of 5.64 s and the GSOA, GOA, MOPSOA, and PSOA models have depicted higher average delay of 5.86 s, 6.13 s, 6.38 s, and 9.87 s respectively. Meantime, on the applied 100 IoT devices, the GEER-DLAD model has employed a least average delay of 6.55 s whereas the GSOA, GOA, MOPSOA, and PSOA models have demonstrated optimal average delay of 8.75 s, 8.87 s, 9.24 s, and 11.95 s respectively. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**No. of IoT**} & \multicolumn{5}{c}{**Average Delay (s)**} \\ \cline{2-6}  & **GEER-DLAD** & **GSOA** & **GOA** & **MOPSOA** & **PSOA** \\ \hline
10 & 2.02 & 2.22 & 2.32 & 2.34 & 2.97 \\ \hline
20 & 2.14 & 2.75 & 3.2  
In order to validate the anomaly detection performance of the RNN-LSTM model, a detailed simulation process was carried out on NSL-KDD dataset [26]. It includes a total of 45,927 samples under DoS attack, 995 samples under R2I attack, 11,656 samples under Probe attack, 52 samples under U2r attack, and 67,343 samples under Normal class.