# Counteracting Selfish Nodes Using Reputation Based System in Mobile Ad Hoc Networks
## 4 Results and Discussion
### Simulation Results  
#### Effect of Area  
The impact of different terrain sizes on the performance of our proposed scheme is evaluated in the presence of 20% of type-I and type-II attackers with mobility of 10 m/s and a pause time of 60 s.  
* Performance in the presence of type-I attackers: The performance in terms of packet drops is given in Figure 2a. It can be seen that OCEAN reported small packet drops against small areas, however, as the area increases our scheme outperforms OCEAN because the benchmark scheme provides a second chance to selfish nodes to join the network. The end-to-end delay of both schemes is shown in Figure 2b. OCEAN reported less delay as compared to our scheme for all terrain sizes because OCEAN uses a rank-based routing mechanism. Figure 2c shows the evil throughput, in which our scheme outperforms the benchmark scheme and recoded low evil throughput. Figure 2d represents good throughput, almost a similar performance can be seen in terms of good throughput. NRL is depicted in Figure 2e; NRL of our scheme is less as compared to OCEAN. Figure 2f represents packet delivery fraction; our scheme produces a higher PDF than OCEAN. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Area & 500, 1000, 1500, 2000 m\({}^{2}\) \\ Pause Time & 10, 20, 30, 40, 50, 60 s \\ Maximum Speed & 5, 10, 15, 20, 25, 30 m/s \\ Number of Nodes & 50 \\ Number of Connections & 30 \\ Application & CBR \\ Packet Size & 64 B \\ Simulation Time & 100, 200, 300, 400, 500, 600 s \\ Mobility Model & Random Waypoint Model \\ Selfish Population & 0\% to 100\% \\ \hline \hline \end{tabular}  
* Evil throughput—determines the throughput offered to misbehaving nodes: \[Evil\;Throughput=\frac{\sum\left(\textit{Received pkts}\right)}{\sum\left(\textit{ Sent pkts by misbehaving}\right)}\] (6)
* Packet delivery fraction—the percentage between the number of packets originated by CBR sources and the number of packets received by CBR sinks at the destination;
* NRL—normalized routing load (NRL) is the fraction of packets communicated at the network layer to the CBR packets at the application layer by the receiver node;
* End-to-end delay—represents retransmission delay, queuing delay, buffering during route discovery, and propagation delay.  
\end{table} 
Table 2: Different simulation parameters. * Performance in the presence of type-II attackers: Figure 3a shows the end-to-end delay, in the small area both schemes produce the same delay, but with an increase in area. OCEAN's delay is going to decrease, because of previously stored routing information. Packet drop is shown in Figure 3b; it can be witnessed that OCEAN has a small packet drop because our scheme suffers from a hard/bad location problem, i.e., our scheme uses consumption to contribution ratio for reputation calculation, thus if a node is located at the boundary, then every time that node will appear as a source node and consequently that node consumption will be increasing, which will decrease a node's  
Figure 2: Performance of the proposed scheme with respect to different sizes of the area against type-I attackers: (**a**) drop packets vs. area, (**b**) delay vs. area, (**c**) evil throughput vs. area, (**d**) good throughput vs. area, (**e**) NRL vs. area, (**f**) PDF vs. area. reputation. Figure 3c represents evil throughput. With all area sizes, evil throughput is zero for both schemes because, during the route establishment phase, type-II attackers do not participate in RREQ. Good throughput is shown in Figure 3d; according to the results with large terrain size our scheme performs well in terms of good throughput as compared to OCEAN. Normalized routing load is presented in Figure 3e; it can be seen that up to 1000 m\({}^{2}\) areas produce the same results; however, with large size area, OCEAN offered high NRL. PDF is depicted in Figure 3f; our scheme delivered more packets as compared to OCEAN.