## 6 Scheduling Algorithm Performance Test Using TLS-VaD
### Results and Discussion
), the biggest difference between \(\lambda_{\text{IRByTSA}}\) and \(\lambda_{\text{FTSA}}\) was 37 timeslots, while between \(\lambda_{\text{IRByTSA}}\) and \(\lambda_{\text{FLSA}}\) the difference was 18 timeslots. In scenario II (Vert. ), the biggest difference between \(\lambda_{\text{IRByTSA}}\) and \(\lambda_{\text{FTSA}}\) was 36 timeslots, while between \(\lambda_{\text{IRByTSA}}\) and \(\lambda_{\text{FISA}}\) it was 25 timeslots. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Number of**} & \multicolumn{2}{c}{**IRByTSA**} & \multicolumn{2}{c}{**FTSA**} & \multicolumn{2}{c}{**FLSA**} \\ \cline{2-7}  & **Horiz.** & **Vert.** & **Horiz.** & **Vert.** & **Horiz.** & **Vert.** \\ \hline
10 & 12 & 12 & 11 & 11 & 9 & 9 \\
20 & 26 & 26 & 27 & 27 & 21 & 21 \\
30 & 40 & 40 & 45 & 45 & 31 & 31 \\
40 & 62 & 62 & 62 & 62 & 43 & 43 \\
50 & 78 & 80 & 78 & 79 & 56 & 59 \\
60 & 95 & 97 & 101 & 113 & 67 & 76 \\
70 & 110 & 122 & 116 & 148 & 81 & 90 \\
80 & 131 & 143 & 144 & 184 & 97 & 107 \\
90 & 152 & 159 & 167 & 204 & 112 & 117 \\
100 & 169 & 175 & 192 & 233 & 124 & 135 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Channel Offset (ChOff) data of IRByTSA, FTSA, and FLSA. Figure 37: Value of \(\lambda\) in IRByTSA, FTSA, and FLSA. In scenario II, the value of \(\lambda_{\text{IRByTSA}}\) was slightly increased, especially in network dimensions above 80 nodes. It is seen on the IRByTSA-Vert graph, which moved away from the IRByTSA-Horiz chart. However, in both scenarios I and II, \(\lambda_{\text{IRByTSA}}\) was always smaller than \(\lambda_{\text{FTSA}}\) and \(\lambda_{\text{FLSA}}\). This indicates that IRByTSA had a high level of stability in the effort to get the best \(\lambda\) value and was superior to FTSA and FLSA in terms of its ability to reach the minimum \(\lambda\) value. Meanwhile, for FTSA, its \(\lambda_{\text{FTSA}}\) value in scenario I and II was much greater than \(\lambda_{\text{IRByTSA}}\). This shows the performance of FTSA in terms of getting a minimum value of \(\lambda\), which was far below that of IRByTSA. The performance of FTSA, which was worse than IRByTSA, even though the way they work is most similar (Table 1 shows that all items are the same except for number 7), was evidence that the mechanism for providing transmission opportunities among child nodes based on turn was an important procedure to have a scheduling algorithm that can give minimum \(\lambda\). As for FLSA, with increased network size, this algorithm performed better in producing \(\lambda\) values than FTSA but not better than IRByTSA. As seen in Figure 37, the value of \(\lambda_{\text{FLSA}}\) was always above \(\lambda_{\text{IRByTSA}}\) and almost always below FTSA, especially for networks with large dimensions. Although \(\lambda_{\text{FTSA}}\) was far above \(\lambda_{\text{IRByTSA}}\) in both scenarios, the \(\lambda_{\text{FTSA}}\) values in scenarios I and II were not very different, whereas in FLSA, the values of \(\lambda_{\text{FLSA}}\) for scenarios I and II had quite large differences. IRByTSA also had the same tendency as FTSA, in that the \(\lambda_{\text{IRByTSA}}\) values for scenarios I and II were not much different. The difference in \(\lambda\) that was not large in scenarios I and II for IRByTSA and FTSA was evidence that the algorithm that gave transmission priority to higher-rank nodes would provide a stable \(\lambda\) value for various network conditions. The value of \(\lambda\) would be directly proportional to the value of the duty cycle, as shown in Figure 38. The duty cycle generated by IRByTSA for the number of nodes ranging from 10 to 100 had the minimum value, which was below 0.5 for both scenarios. With a low duty cycle, the energy consumption of the nodes on the network will be low. Figure 39 shows the number of cycles needed by each algorithm to collect all data in the master node.