# Bio-Inspired Dynamic Trust and Congestion-Aware Zone-Based Secured Internet of Drone Things (SIoDT)
## 5 Results and Discussion
### Performance Analysis according to the Speed and Attacks  
The parameters used for this analysis concerning the varying speed from 50 km/h to 300 km/h are energy efficiency, packet delivery ratio, routing overhead, end-to-end delay, packet loss, and throughput. The performance analysis of the proposed BDTC-SIOVTs is performed using the following attacks. Figure 7 clearly indicates the energy efficiency calculation of the proposed BDTC-SIOVTs according to varying speeds, and it is compared between various attacks. From the graph, it is understood that the performance of proposed BDTC-SIOVTs is high for attacks such as flooding attacks, insider attack, and wormhole attack, and the efficiency of the proposed BDTC-SIOVTs is low in the case of the position falsification attack. The proposed BDTC-SIOVTs is the combination of dynamic trust and hybrid optimization methods which play a better role in the other attacks but still need some betterment in terms of position falsification attacks.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Values** \\ \hline Simulator Version & NS-2.35 \\ Simulation Time & 200 ms \\ Deployment Region & 2000 m \(\times\) 3000 m \\ No of Vehicles & 200 vehicles \\ Antenna Type & Omni-directional Antenna \\ UMTS Threshold & \(-\)94 dBm \\ Transmission Range & 5 Km \\ Queue Type & DropTail \\ Speed & 10 ms\({}^{-1}\) to 35 m.s\({}^{-1}\) \\ Agent Trace & Measured \\ Movement Trace & Measured \\ Router Trace & Measured \\ Transmission Power & 0.500 J \\ Receiving Power & 0.050 J \\ Drone Transmitted Messages & 100 to 200 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Simulation Parameters.  
Figure 7: Energy Efficiency based on varying speed of vehicles.  
The proposed BDTC-SIOVAs produced a high packet delivery ratio with attacks such as flooding attacks and insider attacks. The packet delivery ratio of the proposed network with the wormhole attack and position falsification attack are comparatively low when compared to others, and it is demonstrated in Figure 8.  
Hence, the core idea of the proposed BDTC-SIOVAs is to reduce the overhead so that the idea of dynamic trust-based clustering and the hybrid optimization is combined. The hybrid optimization method greatly helps to reduce the routing overhead even during the presence of attacks in the network. The proposed BDTC-SIOVAs produced a low routing overhead for all the attacks, which is shown in Figure 9.  
The proposed BDTC-SIOVAs produced a low end-to-end delay with attacks such as flooding attacks and insider attacks. The end-to-end delay of the proposed network with wormhole attacks and position falsification attacks is comparatively high when compared others, and it is graphically represented in Figure 10.  
Figure 8: Packet Delivery Ratio based on varying speed of vehicles.  
Figure 9: Routing Overhead based on varying speed of vehicles.  
The proposed BDTC-SIOVAs are the clustered drone-based model that highly concentrates to reduce the loss of packets so that it can support the transmission of confidential messages. The packet loss calculation of the proposed BDTC-SIOVAs is low with all the attacks, and it is shown in Figure 11.  
Hence, throughput is considered to be an important parameter because it represents the overall quantity of data transmission and its ability. So, the perfect network must provide high throughput even in the presence of any kind of attacks. This is highly concentrated in the proposed BDTC-SIOVAs. From Figure 12, it is proved that the throughput utility is high for the proposed BDTC-SIOVAs for all types of attacks. This is the major advantage of the proposed BDTC-SIOVAs method. A detailed discussion of the results is given in the following section.  
Figure 11: Packet Loss based on varying speed of vehicles.  
Figure 10: End-to-End Delay based on varying speed of vehicles.