## 4 Results and Discussion

Table 11: The average % effectiveness of the proposed novel framework for the lifetime of network metric with variations in the harvested energy supply (uniformly). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Lifetime of the Network (Seconds) with Variations in the Harvested Energy Supply** & \multicolumn{3}{c}{**\% Effectiveness of Proposed FRGNWS Framework**} \\  & \multicolumn{3}{c}{**(Random) (mW)**} \\  & & & & **with Existing Frameworks** \\ \hline \multirow{3}{*}{ \begin{tabular}{c} **Harvested Energy Supply** \\ **(Random) (mW)**\(\downarrow\) \\ \end{tabular}  } & **GA-Based** & \multirow{3}{*}{ \begin{tabular}{c} **ABC-Based** \\ **Framework** \\ \end{tabular}  } & **FRGNWS** & \multicolumn{1}{c}{} & **\% Effectiveness of** \\  & & & & **FRGNWS Framework** & **FRGNWS Framework** \\  & & & & **with ABC-Based** & **with GA-Based** \\  & & & & **Framework** & **Framework** \\ \hline \multirow{3}{*}{\ \begin{tabular}{c} 0.3 \\ 0.5 \\ 0.8 \\ 1.5 \\ \end{tabular}  } & 5400 & 6700 & 8600 & 22.09 & 37.21 \\ \cline{1-1} \cline{2-6}  & 6730 & 8340 & 10,200 & 18.24 & 34.02 \\ \hline \multirow{3}{*}{ \begin{tabular}{c} 0.8 \\ 1.1 \\ 1.5 \\ \end{tabular}  } & 8760 & 10,230 & 12,780 & 19.95 & 31.46 \\ \cline{1-1} \cline{2-6}  & 10,450  
Considering Figure 8a, the proposed novel framework once again outperforms the existing frameworks for the delay metric. Further, the role of RNs in reducing the delay is crucial in the network. As the number of RNs are increasing in the network, the data packets can quickly reach the BS. Table 13 exhibits the average % effectiveness of the proposed novel framework compared to the ABC-based framework and GA-based framework as 21.16 and 32.76%, respectively. The proposed novel framework explores the maximum number of node-disjoint routes from all SNs to BS using the minimum number of RNs. The proposed framework provides reliability in routing by selecting the best reliable node-disjoint route from each SN to BS out \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{2}{c}{**End to End Delay (ms) with Variations in the No. of RNs**} & \multicolumn{3}{c}{**\% Effectiveness of Proposed FRGNWS Framework**} \\  & & & & **with Existing Frameworks** \\ \hline \hline \multirow{3}{*}{**No. of RNs \(\downarrow\)**} & **GA-Based** & **ABC-Based** & **FRGNWS** & **FRGNWS Framework** & **\% Effectiveness of** \\  & **Framework** & **Framework** & **Framework** & **with ABC-Based** & **with GA-Based** \\  & & & & **Framework** & **Framework** \\ \hline
6 & 197 & 192 & 182 & 5.21 & 7.61 \\ \hline
12 & 183 & 176 & 161 & 8.52 & 12.02 \\ \hline
18 & 166 & 149 & 124 & 16.78 & 25.30 \\ \hline
24 & 145 & 104 & 83 & 20.19 & 42.76 \\ \hline
30 & 92 & 49 & 22 & 55.10 & 76.09 \\ \hline \multicolumn{2}{c}{Avg. \% Effectiveness\(\rightarrow\)} & & & 21.16 & 32.76 \\ \hline \hline \end{tabular}
\end{table} 
Table 13: The average % effectiveness of the proposed novel framework for the end-to-end delay metric with variations in the number of RNs. Figure 8: The outcomes of the set of simulation experiments conducted with variations in the number of RNs: (**a**) end-to-end delay with variations in the number of RNs; (**b**) energy consumption with variations in the number of RNs. Tables 13 and 14 are given below.