# A Virtualization Infrastructure Cost Model for 5G Network Slice Provisioning in a Smart Factory
## 3 Cost Model
### Cost Model  
Based on the allocated slice types, the further steps required to calculate the costs of the virtual infrastructure are depicted in Figure 3. The demand for a slice type is determined based on the devices from all customers requiring that specific slice type. While some VNFs can be dedicated to each slice type, some VNFs can be common for different slice types. A typical off-the-shelf server is assumed to have a given amount of cores, RAM, storage, and networking capacity, which can be separated into VMs. The VMs can be of different sizes based on the number of cores and their corresponding capacities. Based on the slice customer's device growth, a 'Device forecast' is estimated for the time period under study. Device forecasts can be obtained from industry vertical customers' expectations and by following trends in the telecom market. Based on the 'Device forecast' and the allocated slices, the 'Slice type forecast' depicting the demand for network slices is calculated. In the forecast, the slice size is defined as the number of devices to be supported annually. The 'Slice types' are designed by the slice provider in terms of the virtualized resource requirements per slice type, for each device. The defined 'Slice types' along with the 'Slice type forecast' are used to calculate the total virtualized 'Resource requirements' for each slice type. The 'Resource requirements' are then used for 'VM dimensioning', thus converting the slice provider's slice type input into the number of VMs required for each slice type. The 'VM dimensioning' and the server capacity help estimate the 'Number of servers' required. Any required amount of redundancy can be assumed for the servers  
Figure 2: Slice Type Allocation. per slice type in order to calculate the final 'Number of servers', which helps estimate the supporting racks and cabling, and switches. Furthermore, the following assumptions are made:  
* The VMs are assumed to support a maximum throughput for UP traffic and a maximum number of devices for CP traffic;
* Each VM serves only one VNF, while one VNF might require more than one VM based on capacity demand;
* When a slice requires a dedicated VNF, the VM(s) associated to the VNF are dedicated to that slice. On the other hand, for the common VNFs belonging to multiple slices, the associated VM(s) are common for those multiple slices. In this manner, the VM requirements can be normalized per device for each VNF of each slice type, and then scaled according to the forecasted number of devices each year over 2021-2030. The number of VMs are calculated based on total resource requirements for each CP/UP VNF and the supported CP/UP VM capacity as follows:  
\[\text{Number of VMs per VNF }=\text{ Ceil}\bigg{(}\frac{\text{Total resource req. per VNF}}{\text{VM capacity}}\bigg{)} \tag{1}\]  
The number of UP and CP VMs are then converted to the number of required servers, depending on the deployment scenario. Three deployment scenarios are considered, and the number of servers is calculated as follows:  
In scenario A, only one virtualization infrastructure is deployed in a central cloud or in an edge cloud, with a strategic location for both UP and CP VNFs from which network slices could be served to multiple factories. \[ \begin{split}&\text{Number of servers }(\text{A})\\ &=\text{Ceil}\bigg{(}\frac{\text{No. of UP VMs}}{\text{Server VM capacity}}\bigg{)}+\text{Ceil}\bigg{(}\frac{\text{No. of CP VMs}}{\text{Server VM capacity}}\bigg{)}+\text{Ceil}\bigg{(}\frac{\text{No. of common CP VMs}}{\text{Server VM capacity}}\bigg{)}\end{split}  \tag{2}\]  
Figure 3: Cost Model for Virtualization Infrastructure. In scenario B, each factory deploys its own virtualization infrastructure for UP VNFs, while the CP VNFs for all factories are deployed in a central cloud or in an edge cloud. \[