## 3 Experiments, Comparative Investigations and Results
At the same time, the development of E1, E2 and E5 are channel allocation and timeline scheduling tasks to reduce frame allocation time on the channel. In this regard, E1 and E2 effectively process the timeline slot for scheduling through modified MAC policies and memetic-heuristic scheduling policies, respectively. These techniques perform better than aggressive scheduling policies in dynamic WSNs (E5). Table 9 illustrates the routing benefits of using a standard AODV protocol and hybrid AODV protocol with link-state features. This work identifies the limitations of standard AODV as frequent updates and overhead during network changes. Generally, an AODV protocol performs optimally for reactive updates yet takes maximum overhead for a more dynamic network. At the same time, AODV takes maximum time to update the route \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sensor Node’s Velocity** & **E3** & **E6** & **E7** & **E8** \\ \hline
15 & 458 & 472 & 499 & 523 \\
25 & 499 & 518 & 539 & 557 \\
35 & 514 & 544 & 569 & 589 \\
45 & 553 & 573 & 592 & 603 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Routing delay. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sensor Node’s Velocity** & **E1** & **E2** & **E3** & **E5** \\ \hline
15 & 101 & 101 & 104 & 102 \\
25 & 122 & 117 & 128 & 126 \\
35 & 130 & 134 & 148 & 129 \\
45 & 139 & 145 & 155 & 142 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Scheduler time. information for the whole network regularly. The implementation of both link-state routing models and distance vector models gives fast route updates and reactive route updates, respectively. Especially, the varying velocity of sensor nodes affects the established wireless links frequently. In this case, the uni-protocol system struggles to initiate either global updates or frequent neighbor updates. However, the idea behind AODV-LS supports both reactive and proactive updates (global updates and frequent neighbor updates). Figure 13 compares the efforts of all existing techniques using the metric as the number of packets dropped due to energy shortage (downtime) at a sensor node. This is an important evaluation that relates the amount of residual energy maintained by the node and the active participation of that node itself in data communication. Apart from the continuous oscillations in packet drops produced by each technique, the optimal results are observed for E1, E3, E4 and E5 under various test cycles. As noted in Figure 13, the existing techniques E3 and E4 attain the drops between 35 and 60 as optimal compared to other techniques. At the end, the EOR was taken for performance analysis of all experimented techniques. According to this observation, the higher rates of E2, E3 and E4 show the suitable nature of energy optimization in WSN. On the scope of energy-efficient routing methodologies, many recent works are developed in the research arena [89; 90]. Finally, the practical evaluations are crucially mounting on the considerations of packet drops due to the node's downtime and EOR (Table 10). EOR is the definite attainment of each work towards an energy optimization goal. In this experiment, better energy harvesting (saving) solutions are produced from E3, E4 and E5. Particularly, the effective reduction in computation overhead and retransmission rate gives optimal attainment in EOR. Thus, the EOR of E3 varies between 0.365 and 0.467 during various iterative simulations. In the same manner, E4 attains an EOR from 0.321 to 0.563 as it is using a  
Figure 13: Total number of packets dropped due to sensor node’s downtime. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Sensor Node’s Velocity** & **R1 [AODV]** & **R2 [AODV-LS]** \\ \hline
15 & 169 & 125 \\
25 & 190 & 144 \\
35 & 215 & 151 \\
45 & 246 & 179 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Routing strategies. channel adaptive quality evaluation procedure to initiate data transmission compared to E3. On the next level, E5 attains a better EOR (0.443) due to its load balancing principles compared to other works.