## 4 Experimental Process and Results
In the six experiments, all of the client machines that were deployed had been  
Figure 9: Configuration of experiments. verified as bootable and could enter the Ubuntu Linux. Hence, these six experiments verified the feasibility, efficiency, and scalability of the proposed BT solution. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Number of Clients** & **t\({}_{\text{seq}}\) (1)** & **t\({}_{\text{BT}}\) (2)** & **t\({}_{\text{multicastastast}}\) (3)** & **Ratio (t\({}_{\text{BT}}\)/t\({}_{\text{multicastastast}}\))** \\ \hline  
\hline \hline \end{tabular} Remarks: (1) The total time required by the unicast solution in sequence (secs); (2) the total time required by the BT solution (secs); and (3) the total time required by the multicast solution (secs).  
\end{table} 
Table 2: Total time required to deploy a 50-GB Ubuntu Linux system and applications using the unicast, multicast, and BT solutions. GB: gigabyte. Figure 10: (**a**) Total time and (**b**) average time required for the massive deployment to various clients using the multicast and BT solutions. [PERSON]'s t-test and [PERSON]'s test were performed in order to verify our hypothesis, following the approach used by [PERSON] et al. [84; 85]. These two tests assessed the difference in means (total deployment time in seconds) and variances between the data obtained by using either the BT or the multicast solution. In the tests, the size of the samples was \(n_{1}=32\), \(n_{2}=32\), which was equivalent to the experimental cases. The level of \(\alpha\) was set to 0.050. In addition, t is the t-test for equality of means, and F is [PERSON]'s test for equality of variances [86; 87]. The established hypothesis H\({}_{0}\) stated that the mean time consumed by the massive deployment before the implementation of the BT solution is equal to the mean time consumed by the BT-based solution; H\({}_{1}\) stated that the average time consumption in the massive deployment is lower when the proposed BT solution is implemented. Hypothesis H\({}_{0}\) is rejected, whereas H\({}_{1}\) is proved to be true when the p-value is under 0.050 (significance value); therefore, the system consumes less time from the deployment by using the BT-based solution. As shown in Table 3, the percentage of use after implementing the BT solution was remarkably lower, as the \(p\)-value was much less than 0.050 for both [PERSON]'s test and [PERSON]'s test. In conclusion, the proposed BT system greatly contributes to time savings in massive deployments. To estimate the accuracy of performance enhancement accurately, the current set of samples must be partitioned into a training set and a separate test set. Here, the leave-one-out cross-validation (LOOCV) [88; 89] method was performed, and the results are summarized in Table 4. The time-saving ratio value was obtained by the difference between the time required by the BT and the multicast solutions for the same number of clients. The difference was then divided by the time obtained from the multicast solution. According to the analytic results (refer to Table 4), the total time-saving ratio for 32 experiments was 81.760%. The LOOCV values were derived by leaving the observed time-saving ratio as the validation data, whereas the remaining observations were left as the training data. The difference between the total time-saving ratio and the observed time-saving ratio was then averaged (divided by 31 in this study). As indicated in Table 5, the results derived from the first 10 experiments are not consistent with the remaining 22 experiments. Hence, the accuracy is 22/32 = 68.750%. However, if we neglect the results derived from the first 10 experiments, the accuracy can reach 100%. From the aspect that the proposed P2P-based solution can resolve the scalability problem in large-scale deployment, the result is very reasonable. If more experiments are conducted, it is reasonable to predict that such high accuracy can be sustained. Possible reasons for the phenomenon will also be discussed further in Section 5.1.