# TARCS: A Topology Change Aware-Based Routing Protocol Choosing Scheme of FANETs
## 4 Evaluations and Results
### Impact Analysis of Different TARCS Strategies on Network Performance  
The second experiment is to illustrate different routing strategies can affect different aspects of network performance. This experiment uses three different routing strategies (see Table 4 for details), and the rest of the parameters are the same as Experiment 1. The first strategy is AODV\(\rightarrow\)AODV\(\rightarrow\)DSDV, i.e., in the RWP model the AODV protocol is used, in the RPGM model the DSDV is used, and in the Pursue model the DSDV protocol is used. It is represented by TARCS1 in Table 3. Similarly, TARCS2 is OLSR\(\rightarrow\)AODV\(\rightarrow\)DSDV and TARCS3 is AODV\(\rightarrow\)DSDV\(\rightarrow\)DSDV.  
The network performance under three different types of TARCS strategies is shown in Figure 10. The histogram on the left side of each figure shows the performance for the node speed of 50 m/s, and the right side shows the performance for the speed of 500 m/s.  
It can be seen from Figure 10 that when the node speed is 50 m/s, the packet delivery ratio of the three strategies has little difference and TARCS1 is slightly dominant (TARCS1: 86.1261%, TARCS2: 77.3794%, and TARCS3: 69.3387%). In terms of network throughput, TARCS1 (910.061 Kbps) and TARCS2 (909.755 Kbps) are slightly superior to TARCS3 (766.448 Kbps). In terms of average end-to-end delay, TARCS3 (0.0495 s) is significantly better than TARCS1 (0.0789 s) and TARCS2 (0.05578 s). Regarding average jitter, TARCS3 (0.0483 s) is better than the other two (TARCS1: 0.0708 s and TARCS2: 0.05538 s respectively).  
When the node speed is increased to 500 m/s, the packet delivery ratio of TARCS1 is the highest (sorted in descending order: TARCS1 83.3388%; TARCS3 73.0154%; and TARCS2 69.5115%). The network throughput of TARCS1 is also the highest of the three (sorted in descending order: TARCS1, 881.438 Kbps; TARCS2, 821.2191 Kbps; and TARCS3, 813.157 Kbps). Yet, in terms of average end-to-end delay, TARCS3 has the lowest value (sorted in ascending order: TARCS3, 0.04968 s, TARCS1, 0.07751 s; and TARCS2, 0.1221 s). The average jitter of TARCS3 is also the lowest (sorted in ascending order: TARCS3, 0.04838s; TARCS1, 0.07397 s; and TARCS2, 0.1192 s). None of the network performances is effectively improved by TARCS2.  
The results of the second experiment indicate that using different TARCS strategies can affect different network performance metrics. The indicators affected is related to the characteristics and the appropriate scenarios of each protocol [5]. The AODV protocol is more suitable for RWP scenarios, while DSDV is more suitable for RPGM (g = 1) scenarios. OLSR sits between these two and is very  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Mobility Model** & **TARCS1** & **TARCS2** & **TARCS3** \\ \hline RWP & AODV & OLSR & AODV \\ RPGM (g = 5) & AODV & AODV & DSDV \\ Pursue & DSDV & DSDV & DSDV \\ \hline \hline \end{tabular}
\end{table}
Table 4: Three different schemes of TARCS.  
sensitive to node mobility speed and has higher jitter. The experimental results above also show this feature. Overall, in order to determine which strategy will get the best performance, in addition to the network performance requirements, the network designer must also deeply understand the characteristics of the selected protocol and the suitable scenarios, and make an accurate judgment on the moving scene of nodes.