## 3 Research Scope and Methodology
### Study Methodology
#### 3.3.2 Calculating Method  
Prior to the application of the calculating method, the resource values for VCPU, memory, and disk were measured using hypervisor. The main resource values for each user were measured as shown in Figure 6, which were then are recorded in terms of the VDI resource graph, as shown in Figure 7. In Figure 7, the measured VDI resource values are expressed by using a green line, while red line indicates the average value. These resource values varied when users using a virtual machine, allocated based on the referencing method, made an input and output request. An average value for the measured irregular desktop resource data was calculated. Then, the difference between the average value and the maximum value among these measured values was calculated and denoted as \"\(\alpha\)\". Here, the \(\alpha\) should be either lower than or equal to 30% of the maximum value. In this way, the virtual machine resource values to be allocated to the BIM users were calculated by adding the \(\alpha\) and the mean value of desktop resource data. If the virtual machine resource value allocated to the BIM users through the referencing method was greater than the VDI resource value calculated through the calculating method, the VDI resource value determined by the referencing method was applied; otherwise, the VDI resource value from the calculating method was applied. Finally, if the virtual machine resource value to be allocated to the BIM users through both the referencing method and  
Figure 6: User required performance table: in case of heavy BIM S/W. Figure 7: VDI resource graph. the calculating method was smaller than the performance value required by the users, a resource value, corrected by adding 10% of the correction factor, was allocated to the user. \[q_{i}=\varnothing_{1}\ P_{i1} +\varnothing_{1}\ P_{i2}+\varnothing_{1}\ P_{i3}+\ldots\] \[=\sum\limits_{j=1}^{k}\varnothing_{j}\ P_{ij}\] \[\overline{q}=\frac{1}{n}\ \sum\limits_{i=0}^{n}q_{i}\] \[C=\overline{q}+\alpha\alpha=q_{max}+(q_{max}-\overline{q})\] \[\alpha\leq q_{max}\times 30\%\] \[But,\ C\ \leq q_{max}\to C=q_{max}\times 1.1\]  
**4**_qmax_**1.1. ** Correction coefficient for application complexity applied, [PERSON] (2007) [28]. Table 5 shows the resource allocation design based on BIM desktop. The calculation steps to obtain final resource values can be summarized in three steps:  
Step 1: Add the \"\(\alpha\) = the maximum value of the measured resource values minus the average value\" to the \"average value of the resource values measured through Server Management\" to obtain the resource value;  
Step 2: Apply only 30% of the \(\alpha\) value in the case where the \(\alpha\) value exceeds 30% of the maximum measured resource value;  
Step 3: If the resource value required by the user derived in Step 2 is insufficient, then increase the application complexity correction factor by 10%. Based on the algorithm generated by both the referencing method and the calculating method, a cloud service platform was developed using OpenStack, and the platform was named KBimVdi. It allowed a user given an ID/PW to gain access to the VDI system irrespective of the type of a device he/she was using under any environment with Internet access. ID/PW could be set and obtained by logging in to the BIM Management under Flavors while in administrator mode (Table 6). When the BIM user selected four categories (Software, Work Type, Project, and Phase of Design), the user's virtual machine specification was automatically set based on the sizing algorithm of the BIM-based VDI server. In addition, it had an advantage with its easy management because virtual machine resources were allocated by applying optimized correction values under the BIM environment.