# VNF-Enabled 5G Network Orchestration Framework for Slice Creation, Isolation and Management
## 5 Simulation Results and Discussion
### SMART Scheme  
In order to improve the performance of SIRA scheme-based resource allocation, our SMART scheme is being implemented in its current form. As previously stated, this scheme is responsible for four different tasks depending on the information it receives. With this scheme, the unsuccessful NSRs are given the greatest amount of attention to improve resource efficiency and acceptance ratios overall. The SMART scheme seeks to determine the most effective method of turning unsuccessful NSRs into successful ones. This function starts the node allocation process for unsuccessful NSRs when only one slice of an NSR is unsuccessful among the three different types of NSR slices that are available. It is necessary to treat the nodes in the unallocated slice of NSR as Alien Nodes, and the process of searching for node provisioning in the other two PI slices is known as inner slicing. The Alien Nodes are kept in unassociated slices until they are able to locate the provisioning in their associated primary interface slice. SMART scheme performance is demonstrated by executing the scheme under identical operating conditions, with nodes of PI ranging from 100 to 300 and NSRs ranging from 5 to 35. Figure 10 depicts the resource efficiency obtained under various conditions by using SIRA and SMART, as well as the results of the study.  
On the basis of the graph, it is clear that the SMART scheme contributes to a reasonable increase in resource efficiency. To serve 20 NSRs, it provides service to 142/126/132 nodes in the eMBB, mMTC, and uRLLC networks. SIRA scheme, on the other hand, could serve 142 eMBB nodes, 126 mMTC nodes, and 132 uRLLC nodes with the same number of NSRs. The SMART scheme achieves a greater improvement in serving eMBB, mMTC, and uRLLC nodes than the SIRA scheme. This results in a physical infrastructure that can serve a greater number of NSRs than any other resource allocation method. It can also be justified by comparing the acceptance ratio and execution time of two schemes, which are depicted in Figures 11 and 12, respectively, to see how they compare.  
Figure 10: Resource efficiency of SMART with SIRA.  
Figure 9: Execution time of SIRA with other algorithms.  
According to the figures, the SMART scheme generates the optimal solution more quickly than any other algorithm while maintaining a higher acceptance ratio. Also, the figures demonstrate that the acceptance ratio of the SMART scheme has increased significantly as a result of the scheme's execution taking a comparatively short amount of time. With 10 NSRs and 300 reachable PI nodes, the proposed method can achieve a maximum acceptance ratio of 1. A minimal acceptance ratio of 0.89 is achieved when 35 NSRs and 100 accessible nodes are used. Moreover, the amount of CPU utilised and BW consumed by SMART is increased compared to SIRA schemes as shown in Figure 13. This current scheme can handle a maximum of 10,568 CPUs and a minimum of 3058 CPUs, and for bandwidth, a maximum of 31,628 and a minimum of 8340 under the PI with 100 and 300 nodes.  
Figure 11: Acceptance ratio of SMART with SIRA.  
Figure 12: Execution time of SMART with SIRA.  
Figure 13: CPU and bandwidth utilization of SMART with SIRA.