## 4 Results and Discussion
Tables 11 and 12 give more clarity on the effectiveness of the proposed novel framework by providing the average % effectiveness compared to the existing frameworks, considering the metric the lifetime of the network. Considering Figure 7a, this figure tries to narrate the effectiveness of the proposed novel framework with existing frameworks, considering the network lifetime metric under variations in the harvested energy supply uniformly. Table 11 exhibits the average % effectiveness of the proposed novel framework compared to the ABC-based framework and GA-based framework as 15.01% and 23.47%, respectively. The network lifetime increases gradually when a uniform supply of harvested energy is considered. The reason for this outstanding performance of the proposed novel framework is the optimal energy efficiency of this framework. Although the energy-harvesting capability in the network maintains a continuous supply to nodes, optimization of energy use is needed for enhanced network lifetime, and the proposed novel framework shows this efficacy. The existing frameworks are unable to show strength towards energy efficiency and results in a lower network lifetime in this case. Figure 7: The outcomes of the set of simulation experiments conducted with variations in the harvested energy supply uniformly as well as randomly: (**a**) lifetime of the network with variations in the harvested energy supply (uniformly); (**b**) lifetime of the network with variations in the harvested energy supply (randomly). Tables 11 and 12 are given below. Considering Figure 7b, although the network lifetime also increases under variations in the harvested energy supply (randomly), the results are somewhat lower when compared with the uniform supply of harvested energy. Table 12 exhibits the average % effectiveness of the proposed novel framework compared to the ABC-based framework and GA-based framework as 20.19% and 32.68%, respectively. The proposed novel framework unveils the efficacy for the network lifetime metric with existing frameworks due to energy efficiency capabilities that are lacking in the existing frameworks. Category 4: The fourth set of simulation experiments were carried out under this category. We varied the number of RNs and recorded the outcomes on the end-to-end delay and energy consumption. Figure 8a,b illustrate the efficacy of the proposed novel framework (FRGNWS) compared to the existing frameworks, namely, the ABC-based framework and GA-based framework. Tables 13 and 14 give more clarity on the effectiveness of the proposed novel framework by providing the average % effectiveness compared to the existing frameworks, considering each metric one by one, namely, the end-to-end delay and energy consumption. \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}{**(Uniform) (mW)**} & \multicolumn{1}{c}{} \\  & & & & **with Existing Frameworks** \\ \hline \multirow{3}{*}{\begin{tabular}{c} **Harvested Energy Supply** \\ **(Uniform) (mW)**\(\downarrow\) \\ \end{tabular} } & **GA-Based** & \multirow{3}{*}{\begin{tabular}{c} **ABC-Based** \\ **Framework** \\ \end{tabular} } & **FRGNWS** & \multicolumn{1}{c}{} & **\% Effectiveness of** \\  & & & & **with ABC-Based** & **FRGNWS Framework** \\  & & & & **with Existing Frameworks** \\ \hline \multirow{3}{*}{\begin{tabular}{c} 0.4 \\ 0.8 \\ 1.2 \\ 1.6 \\ 2 \\ \end{tabular} } & 10,450 & 11,500 & 13,950 & 17.56 & 25.09 \\ \hline \multirow{3}{*}{\
\begin{tabular}{c} 1.6 \\ 2 \\ \end{tabular} } & 12,340 & 14,230 & 16,450 & 13.50 & 24.98 \\ \hline \multirow{3}{*}{
\begin{tabular}{c} Avg. \% Effectiveness\(\rightarrow\) \\ \end{tabular} } & 14,987 & 16,870 & 20,000 & 15.65 & 25.07 \\ \cline{1-1} \cline{2-6}  & & & & 15.01 & 23.47 \\ \hline \hline \end{tabular}
\end{table}