# Classification and Merging Techniques to Reduce Brokerage Using Multi-Objective Optimization
## 4 CMRBC: System Model
**Scenario 3:**_There are fewer jobs than virtual machines._

If the number of small jobs is less than the number of VMs, then VMs remain idle, waiting for jobs. This leads to the underutilization of resources. Then, merging those small jobs still reduces the creation of VMs. For example, if there are 10 small jobs and there are 50 VM, and out of 50 VMs, only 10 are utilized, and 40 VMs remain idle. **Scenario 4:**_When we merge the number of jobs into one job, if any job in the merged jobs fails to be executed due to some reason, the remaining merged jobs cannot be executed. This leads to the incomplete execution of jobs and also affects the other jobs. For example, \(J_{1}\) and \(J_{5}\) are merged, and if \(J_{1}\) is not executed due to some problem, then \(J_{5}\) cannot be executed, even though it is possible to execute it._

## 5 Experimental Results

The experiment was run on a cloud simulator tool, version 3.03, and the configuration of the computer was as follows: CPU (64-bit, Intel Pentium(R) i7 CPU 2.9 GHz) with 16 GB RAM and 2 TB hard disk and Net beans 8.1 editors, coded in java language and Intel Core i7 processor environment, with a 100 GB Memory. The CMRBC algorithm implemented both the scheduling of the instant VM allocation and the classification and merging techniques using a Twitter data set, the size of which was 10 GB, with four jobs types: small, medium, large, and extra-large. The size of the job was predefined as small being 50 MB, medium being MB, large being 150 MB, and a size greater than 150 was considered an extra-large job. The arrival of a job was based on the Poisson distribution, as shown in \[Cl=\Sigma^{\text{ k}}\ _{\text{ i}}=\text{1}\ larger\_job\_i \tag{9}\]3

The experimental results of a workload for 12 jobs using classification and merging techniques are shown in Table 3, and the internal structure of job allocation to virtual machines is shown in \[Cl=\Sigma^{\text{ k}}\ _{\text{ i}}=\text{1}\ larger\_job\_i \tag{9}\]4 The arrival time and deadline of jobs was given previously, as shown in \[Cl=\Sigma^{\text{ k}}\ _{\text{ i}}=\text{1}\ larger\_job\_i \tag{9}\]5 The goal of this model was to classify jobs based on the size of them \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**12 Jobs** & **Job Size** & **Classification** & \begin{tabular}{c} **VM** \\ **Number** \\ \end{tabular} & \
\begin{tabular}{c} **Arrival** \\ **Time** \\ \end{tabular} &
\begin{tabular}{c} **Deadline** \\ **Time** \\ \end{tabular} \\ \hline
1 & 10 & Small & VM1 & 0 & 150 & 110 \\ \hline
2 & 50 & Small & VM1 & 0 & 150 & 110 \\ \hline
3 & 200 & Extra-large & VM4 & 0 & 250 & 249 \\ \hline
4 & 100 & Medium & VM3 & 120 & 260 & 252 \\ \hline
5 & 35 & Small & VM1 & 122 & 160 & 158 \\ \hline
6 & 40 & Small & VM2 & 138 & 172 & 172 \\ \hline
7 & 150 & Large & VM5 & 140 & 150 & 149 \\ \hline
8 & 75 & Medium & VM3 & 160 & 175 & 175 \\ \hline
9 & 15 & Small & VM1 & 170 & 152 & 110 \\ \hline
10 & 50 & Small & VM1 & 177 & 280 & 110 \\ \hline
11 & 50 & Small & VM1 & 182 & 190 & 110 \\ \hline
12 & 25 & Small & VM2 & 190 & 200 & 199 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Example of the classification and merging technique workload of 12 jobs. using threshold values and merging the jobs based on the virtual machine capacity. The table shows which classified and merged jobs fit which VM type. The arrival time and deadline time were given as soon as the job is submitted to the classifier. The classification and merging of jobs were only completed for smaller jobs. Jobs 1, 2, 5, 6, 9, 10, 11 were classified as small because the size of each job was less or equal to 50 MB, Job\({}_{3}\) was extra-large, where the job size was 200 MB, job4,8 were medium, where is the sizes were less than or equal to 100 MB, and job\({}_{7}\) and job3 were large and were broken down into three small jobs and assigned toVM4. The obtained results are shown in Table 3.

Here, the cost of the broker represents the number of virtual machines that create a job.