# TARCS: A Topology Change Aware-Based Routing Protocol Choosing Scheme of FANETs
## 4 Evaluations and Results
### Validation of TARCS
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Perceptual** & **Actual Mobility** & \multicolumn{3}{c}{**Node Speed = 50 m/s**} & \multicolumn{2}{c}{**Node Speed = 500 m/s**} & \multicolumn{1}{c}{**Route**} \\ \cline{3-6}
**Moment** & **Model** & **TCD(\(t\))** & **Judged model** & **TCD(\(t\))** & **Judged model** & **Protocol** \\ \hline
50 & RWP & 2.078 & RWP & 0 & RWP & AODV \\
100 & RWP & 15.459 & RWP & 842.592 & RWP & AODV \\
150 & RWP & 34.364 & RWP & 782.536 & RWP & AODV \\
200 & RPGM (g = 5) & 177.845 & RPGM & 589.106 & RWP & AODV \\
250 & RPGM (g = 5) & 560.596 & RPGM & 2513.24 & Pursue & DSDV \\
300 & RPGM (g = 5) & 658.254 & RPGM & 678.321 & RWP & AODV \\
350 & RPGM (g = 5) & 493.418 & RPGM & 2102.88 & Pursue & DSDV \\
400 & Pursue & 1963.96 & Pursue & 4144.1 & Pursue & DSDV \\
450 & Pursue & 974.397 & RPGM & 2042.52 & Pursue & DSDV \\
500 & Pursue & 3800.78 & Pursue & 2312.88 & Pursue & DSDV \\
550 & Pursue & 2332.39 & Pursue & 4482.67 & Pursue & DSDV \\
600 & Pursue & 4786.97 & Pursue & 3666.45 & Pursue & DSDV \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The topological change degree (TCD) perception results and route protocol choosing scheme of Experiment 1. The cause of the error is likely to be the following factors. The threshold setting is not reasonable enough, and the time of each mobility model is not long enough, so the mobility model is not very stable when the nodes move at high speed. Figure 9 illustrates the comparisons of performance metrics, including the packet delivery ratio, the network throughput, the average end-to-end delay and the average jitter under two different node speeds (50 m/s and 500 m/s) with the TARCS (assume that all mobility models are accurately identified)and with other routing protocols. It can be seen from Figure 9a that when node speed is 500 m/s, the packet delivery ratio is 58.9435% only with OLSR, 55.4443% only with DSDV, 74.9448% only with AODV, and rises to 83.3388% with the TARCS. Figure 9b shows the network throughput comparison with and without TARCS under different node speeds. Taking the speed of 500 m/s as an example, the network throughput is 666.716 Kbps when only OLSR is used, 701.095 Kbps when DSDV is only used, 862.448 Kbps when AODV is only used, and 881.438 Kbps when the TARCS scheme is used. Network throughput is increased by 32.2%, 25.7%, and 2.2%, respectively, compared to using only OLSR, DSDV, and AODV. Figure 9c shows the average end-to-end delay comparison. Regardless of the rate, the average end-to-end delay is different from the first two performance metrics. Using the TARCS strategy chosen for this experiment, the average end-to-end delay of the network is not the smallest, but between the highest 0.141 s (AODV) and the lowest 0.032 s (DSDV), and is also higher than the OLSR of 0.06 s with the node speed of 500 m/s. Figure 9: Performance comparisons with and without the TARCS: (**a**) packet delivery ratio; (**b**) network throughput; (**c**) average end-to-end delay; (**d**) average jitter. The comparison result of the average jitter is similar to that of the delay, as is shown in Figure 9d. It is between the highest value of 0.149 s (only with AODV) and the lowest value of 0.0383 s (only with DSDV) with the node speed of 500 m/s. The reason why the advantage of TARCS is not obvious when the speed is low is that the topology change of the network is not obvious when the node speed is low. The results of first experiment show that:  
* In a complex scenario, using the TARCS strategy will have a certain impact on network performance. * Using the same TARCS strategy at different node speeds has a different impact on network performance. * In the TARCS strategy, the setting of \(\mathrm{TCD_{TH}}\) is very important and should be performed in advance.