# Secured VM Deployment in the Cloud: Benchmarking the Enhanced Simulation Model
## 6 Observations
### Assessment of CTU Usage  
Central processing unit (CPU) utilization, sometimes known as CTU utilization, is the term used to describe the total amount of processing time needed to run a program in cloud computing. Applications that run in the cloud usually require virtual machines (VMs) located in server zones. Once assigned, these virtual machines (VMs) can accomplish a wide range of tasks that correspond with the host's processing needs. Minimizing CTU utilization is necessary for efficient resource use in cloud environments because it ensures that computing resources are used to their fullest potential. Therefore, reducing CTU consumption is essential to improving overall resource efficiency and making the cloud infrastructure capable of supporting a wide variety of workloads and operations.  
In Figure 3, a graphical representation of the CTU usage between the proposed work and the previous studies is exhibited. As shown in Table 3, for 10 VMs: TF-MFA perpetrates a CTU utilization of 886.2, which is much lower than ILWOA (5692.2), WOGA (4712.1), KH (1280.8), CSA (1253.9), ACO (1323.2), and ABC + BA (935.61). This suggests that TF-MFA surpasses the other algorithms in the context of resource utilization for this VM count. For 20 VMs: TF-MFA demonstrates a CTU utilization of 1228.8, which is on descending analogized to ILWOA (5071.9), WOGA (3290.9), KH (1790), CSA (1202.9), ACO (1535.9), and ABC + BA (1679.2). TF-MFA exemplifies better resource utilization efficiency for this VM count, as well. For 30 VMs: TF-MFA attains the lowest CTU utilization value of 963.14 compared with ILWOA (2212.3), WOGA (3215.1), KH (2665.1), CSA (1253.9), ACO (1094.3), and ABC + BA (1597.1). This reveals that TF-MFA provides the most efficient utilization of computational resources for 30 VMs. For 40 VMs and 50 VMs: TF-MFA invariably harbors lower CTU utilization values compared with ILWOA, WOGA, KH, CSA, ACO, and ABC + BA, although the differences vary for each algorithm.  
The comprehensive analysis clearly shows that the twin fold moth flame algorithm (TF-MFA) model performs better than other algorithms in terms of central processing unit (CTU) use, exhibiting greater efficiency at different counts of virtual machines. This validation highlights how well the TF-MFA model works to optimize resource allocation and improve overall cloud computing environment virtual machine placement efficiency. The findings support the model's ability to achieve more efficient use of computing resources and highlight its promise as a cutting-edge and practical approach to handling the difficulties associated with placing virtual machines in a variety of dynamic computing settings.  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline
**No. of VM** & **TF-MFA** & **ILWOA** & **WOGA** & **KH** & **CSA** & **ACO** & **ABC + BA** \\ \hline
10 & 886.2 & 5692.2 & 4712.1 & 1280.8 & 1253.9 & 1323.2 & 935.61 \\
20 & 1228.8 & 5071.9 & 3290.9 & 1790 & 1202.9 & 1535.9 & 1679.2 \\
30 & 963.14 & 2212.3 & 3215.1 & 2665.1 & 1253.9 & 1094.3 & 1597.1 \\
40 & 1135 & 3121.6 & 1858.5 & 1675.3 & 1501.7 & 1614.7 & 1598.9 \\
50 & 1389.7 & 5818.5 & 2418.1 & 2246.8 & 1139.7 & 1311.8 & 985.04 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Portrays CTU allocation for various VMs in proposed and existing models.