# A New Lightweight Watchdog-Based Algorithm for Detecting Sybil Nodes in Mobile WSNs
## 5 Simulation Results and Performance Evaluation
### Simulation Results
#### 5.3.1 Evaluation  
The TDR and FDR of the new algorithm are evaluated by setting up five tests. These tests differ by the choice of the independent and fixed parameters. To ensure the validity of the results, each point is the average of 30 repetitions to achieve a 95% confidence interval. At the end, the three remaining measures of performance, memory/communicational overhead, and computational load are discussed qualitatively. * **Test 1:** This test is designed to evaluate the new algorithm's TDR and FDR against the number of movement steps for different number of Sybil IDs as a parameter varying from 8 to 20. The value of the remaining parameters are fixed as they appear in Table 1. Figure 7a shows that TDR increases as time goes by. This is completely expected since more information is collected in longer periods of time. After 120 movement steps, for any number of Sybil IDs, good detection rates of at least 95% are achieved. Similarly, we expect FDR to improve by collecting more information over time towards higher movement steps. As Figure 7b illustrates, regardless of the number of Sybil IDs, FDR sufficiently nears zero at movement steps close to 160. * **Test 2:** In this test, TDR and FDR have been evaluated against the number of movement steps for different number of normal nodes varying from 100 to 400 (The values of the remaining parameters are fixed as they appear in Table 1). As shown in Figure 8a and very consistent with the results of Figure 7a, good TDR results are obtained after 120 number of movement steps, no matter what the number of normal nodes is Similar to what we observed in Figure 7b of Test 1, Figure 8b shows that FDR decreases with increasing movement steps until reaching almost zero at movement steps close to 200. * **Test 3:** Through this test it is illustrated how TDR and FDR are affected by varying the number of malicious nodes from 1 to 10. The fixed parameters are \(S=10,W=4\), and \(N=200\) ( for the values of other parameters refer to Table 1). In Figure 9a,b, almost perfect TDRs and FDRs are achieved for all number of malicious nodes from movement steps greater than or equal to 120 on. \begin{table}
\begin{tabular}{l c c} \hline \hline
**Parameter** & **Value/Fixed** & **Value/Variable** \\ \hline No. of normal nodes, \(N\) & 300 & 100 \(\rightarrow\) 400 \\ No. of watchdog nodes, \(W\) & 4 & 4 \(\rightarrow\) 10 \\ No. of Sybil IDs/malicious node, \(S\) & 14 & 10 \(\rightarrow\) 22 \\ No. of malicious nodes, \(M\) & 5 & 1 \(\rightarrow\) 10 \\ Max speed of nodes & 5 m/s & - \\ Topology size & 100 m \(\times\) 100 m & - \\ Wireless radio range & 10 m & - \\ Simulation time step & 50 ms & - \\ Sybil threshold, \(T_{s}\) & 1 & - \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Simulation Parameters. * **Test 4:** Values of TDR and FDR against the number of Sybil IDs for different number of watchdog nodes is the subject of this test. The results correspond to movement step equal to 160 where the system has already reached its steady state. As before, the other fixed parameters are as they appear in Table 1. Figure 10a suggests that while increasing the number of WDs results in better TDRs, the improvement is negligible after some case-dependent WD population (\(W=6\) and greater). Figure 10b illustrates perfect FDR at the steady state for all choices of WD population. * **Test 5:** In this test, the effect of scalability on the TDR/FDR performance of the proposed algorithm is verified (Figure 11). To make it a fair comparison, all node populations (normal, malicious, and watchdog) grow proportionally with the network area. The value of population parameters and the snapshot instance (Movement step) are mentioned in the figure. The maximum network size adopted is constrained by the limitations of J-SIM. The other fixed parameters are as they appear in Table 1. The TDR/FDR results of Figure 11 show very insignificant variations with respect to the network size.