# Real-Time Evaluation of the Improved Eagle Strategy Model in the Internet of Things
## 5 Testing and Validation
### Evaluate the Execution Time for Selecting the Services from the Large-Scale Repository  
The existing method was simulated using NetLogo as a proof of concept. The results were compared to the proposed approach to determine the milliseconds (ms) needed to choose a service from the huge repository. The simulation allowed the same number of datasets to reflect the number of WS in the same environment regardless of the methodologies utilized. A large-scale repository can be mimicked by declaring the number of services. The simulation was repeated three times for each number of WS to get an approximate estimate of the value of search time, and the mean value was calculated from the results. Equation (12) below shows the formula for calculating the mean value. \[Mean=\frac{\sum\mathit{of\ the\ terms}}{number\ of\ terms} \tag{12}\]  
Table 4 provides an overview of the time required (in milliseconds) to select the high-fitness value service for the Whale Optimization Algorithm (WOA), followed by a graphical illustration shown in Figure 17. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{3}{c}{**Whale Optimization Algorithm (WOA)**} \\ \hline
**NOS 1** & \multicolumn{3}{c}{**Time Taken (ms)**} & \multicolumn{1}{c}{**Mean (ms)**} \\ \hline
300 & 19.246 & 20.336 & 15.799 & 18.4603 \\
400 & 21.341 & 20.811 & 21.669 & 21.2737 \\
500 & 24.71 & 27.527 & 24.506 & 25.5810 \\
600 & 32.749 & 31.816 & 28.643 & 31.0693 \\
700 & 33.46 & 32.224 & 33.792 & 33.1587 \\
800 & 47.332 & 38.262 & 37.71 & 41.1013 \\
900 & 44.689 & 40.07 & 42.056 & 42.2717 \\
1000 & 56.176 & 45.578 & 44.305 & 48.6863 \\
2000 & 84.539 & 94.24 & 82.707 & 87.1620 \\
3000 & 125.118 & 125.171 & 124.55 & 124.9463 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Time taken to select the service by WOA. Figure 16: Phases of Testing and Validation. Table 5 below shows the overview of the time required (in milliseconds) to select the service for the proposed method, the Improved Eagle Strategy, and a graphical illustration is shown in Figure 18. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{3}{c}{**Eagle Strategy (ES)**} \\ \hline
**NOS 1** & \multicolumn{3}{c}{**Time Taken (ms)**} & \multicolumn{3}{c}{**Mean (ms)**} \\ \hline
300 & 4.354 & 4.912 & 5.178 & 4.81467 \\
400 & 5.291 & 5.55 & 5.832 & 5.55767 \\
500 & 5.993 & 6.118 & 6.487 & 6.19933 \\
600 & 7.21 & 7.45 & 7.628 & 7.42933 \\
700 & 7.571 & 7.669 & 7.903 & 7.71433 \\
800 & 7.981 & 8.321 & 10.484 & 8.92867 \\
900 & 9.531 & 9.779 & 10.798 & 10.03600 \\
1000 & 12.328 & 11.965 & 13.354 & 12.54900 \\
2000 & 25.892 & 28.945 & 30.456 & 28.43100 \\
3000 & 125.118 & 125.171 & 124.55 & 124.9463 \\ \hline \hline \end{tabular}  
* Number of services.  
\end{table} 
Table 5: Time taken to select the service by ES. Figure 17: Graphical illustration for WOA service selection. Figure 18: Graphical illustration for ES service selection. Table 6 below shows the overview of the time required (in milliseconds) to select the service for the proposed method, the Improved Eagle Strategy, and a graphical illustration is shown in Figure 19.  
To calculate the amount of time needed to choose a service, the proposed approach, known as the IES, was judged against two other bio-inspired methods that already exist: WOA and ES. The above table and graph for ES, WOA, and the IES show that the suggested method revealed that the IES can select a service from a large-scale repository in a shorter amount of time. Figure 19 below compares the time taken for the three methods tested in the same environment using NetLogo Simulation. The IES model results were better than those for the WOA and ES, as shown by the comparison result in Figure 20. As can be concluded by the author [7], the ES has the potential to select a service faster than another service, but when the search space is bigger, the time taken to select a service is less. At the same time, the ES only focuses on the non-functional attributes of WS. The IES, on the other hand, focuses on both functional and non-functional attributes.