# Towards Efficiently Provisioning 5G Core Network Slice Based on Resource and Topology Attributes
## 6 Conclusions  
5G will be a disruptive technology in many ways. It has the potential to shakeup the telecommunications industry but would require significant investments. Consumers, both businesses and individuals, expect new opportunities from massive, ultra low latency and high density Internet of Things, as a run up to ambitious use cases such as smart cities and autonomous vehicles. The potential of 5G can only be truly realized if telecommunications service providers build in economies in the new deployments. Network slicing would be a key factor in achieving increased efficiencies and revenues through service specific offerings.  
We have worked on the slice-provisioning problem by taking into account both the slice node provisioning and the slice link provisioning aspects. Accordingly, we have proposed a two-stage slice-provisioning algorithm called RT-CSP. As far as provisioning of slice nodes is concerned, our method takes into account the compute capacities, link bandwidths, degree centrality, and closeness centrality for comprehensive evaluation and ranking of nodes. These amount to jointly considering the local and global network resource attributes along with the topology attributes. Along with the heuristic slice node provisioning algorithm, RT-CSP uses the \(k\)-shortest path based slice link provisioning algorithm. An enhancement developed by us called RT-CSP+, based on _minMaxBWUtilHops_ strategy designed by us, improves the performance further by selecting the physical path that has the minimum product of the maximum link bandwidth utilization and its hop count from the candidate physical paths obtained by the \(k\)-shortest path algorithm.  
Extensive evaluations were carried out to compare both of our algorithms with other state-of-the-art algorithms and prove that the proposed algorithm does increase the slice request acceptance ratio and consequently the revenue of the network infrastructure provider. As far as acceptance ratio is concerned, both RT-CSP and RT-CSP+ perform better than other algorithms with the latter consistently giving the best performance. As the slice request arrival rate increases, the acceptance ratio of all the algorithms goes down but RT-CSP+ retains its supremacy. In terms of provisioning revenue, RT-CSP+ excels in long-term average slice provisioning revenue and revenue-to-cost ratio. Both RT-CSP and RT-CSP exhibit better revenue performance than other algorithms as the arrival rate increases. These results verify that our algorithms can comprehensively optimize node provisioning using the resource and topology attributes.  
We are enthused with the good performance of our algorithms and, in the future, we plan to propose an efficient provisioning solution for latency-sensitive slices to satisfy low-latency 5G applications.  
Figure 9: (**a**) Long-term average slice provisioning revenue in the different sizes of substrate network scenario; and (**b**) slice provisioning revenue-to-cost ratio in the different sizes of substrate network scenario.  
**Author Contributions:** Conceptualization, X.L. and R.J.; Methodology, X.L., R.J. and C.G.; Software, X.L.; Validation, X.L.; Writing--Original Draft Preparation, X.L. and L.G.; Writing--Review and Editing, all authors; and Supervision, C.G. and R.J.  
**Funding:** This work was supported by the NPRP grant #NPRP 8-634-1-131 from the Qatar National Research Fund (a member of The Qatar Foundation), NSF grant #CNS-178929, Huawei Technologies, and China Scholarship Council (No. 201506270075).  
**Conflicts of Interest:** The authors declare no conflict of interest.