## 4 Experiments and Results
### Average Fragment Size by File Size  
In this section, we consider the size of fragments with respect to the original file size, to add another relevant element for analysis and comparison with other new future solutions, which will carry out similar approaches. In Figure 10, we show how the average size of the fragments increases as the file size increases. As in the previous cases, the \(x\)-axis represents the file size, while the \(y\)-axis shows the fragment size in bytes.  
This size can have significant impacts on system performance. Smaller fragments can improve space management and reduce waste in scenarios with files of varying sizes, but they can also increase management overhead. Conversely, larger fragments can be beneficial for read and write speeds on storage devices that handle larger data blocks better. Evaluating the optimal fragment size is essential to balancing efficiency and performance.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**System 5** & **Mean (s)** & \(\sigma\) **(s)** & **Min (s)** & **Max (s)** \\ \hline
1 kb & 0.0054 & 0.0067 & 0.0013 & 0.0536 \\ \hline
100 kb & 0.0078 & 0.0063 & 0.0020 & 0.0291 \\ \hline
1 mb & 0.0057 & 0.0047 & 0.0017 & 0.0493 \\ \hline
10 mb & 0.0083 & 0.0096 & 0.0026 & 0.8007 \\ \hline
100 mb & 0.0160 & 0.0138 & 0.0061 & 1.0324 \\ \hline \end{tabular}
\end{table}
Table 7: Analytical results for loading time, including fragmentation, encryption, and saving, in different physical architectures running MuReQua DeSSE with hardware named System 5.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**System 6** & **Mean (s)** & \(\sigma\) **(s)** & **Min (s)** & **Max (s)** \\ \hline
1 kb & 0.0137 & 0.0057 & 0.0070 & 0.0282 \\ \hline
100 kb & 0.0206 & 0.0054 & 0.0109 & 0.0371 \\ \hline
1 mb & 0.0222 & 0.0075 & 0.0114 & 0.2175 \\ \hline
10 mb & 0.0236 & 0.0095 & 0.0130 & 0.3390 \\ \hline
100 mb & 0.0327 & 0.0132 & 0.0162 & 0.2395 \\ \hline \end{tabular}
\end{table}
Table 8: Analytical results for loading time, including fragmentation, encryption, and saving, in different physical architectures running MuReQua DeSSE with hardware named System 6.  
Based on the considerations presented, it will be valuable in the future to conduct a dedicated optimization study on the topic discussed here. Specifically, assessing the impact  
Figure 10: The figure indicates how large the data blocks are into which a file is divided during the saving process.  
Figure 9: These charts represent the distribution of average creation and saving times of file fragments in relation to their size.  
of fragment size on system performance can provide insights into achieving a balance between efficiency and performance. Smaller fragments may enhance space management and minimize waste, particularly when dealing with files of varying sizes, although they could lead to increased management overhead. On the other hand, larger fragments may optimize read and write speeds on storage devices that are better suited for larger data blocks. A focused study could help determine the optimal fragment size for various use cases and system architectures.  
Moreover, to better handle video and audio formats, it will also be essential to conduct studies aimed at large files, specifically those greater than 100 MB and up to 5-10 GB, within the context of Big Data. Such investigations will provide valuable insights for optimizing the management and performance of large media files in complex data environments.