Radio Access Network Function Placement Algorithms in an Edge Computing Enabled C-RAN with Heterogeneous Slices Demands

Network slicing provides a scalable and flexible solution for resource allocation with performance guaranty and isolation from other services in the 5G architecture. 5G has to handle several active use cases with different requirements. The single solution to satisfy all the extreme requirements requires overspecifies and high-cost network architecture. Further, to fulfill the diverse requirements, each service will require different resources from a radio access network (RAN), edge, and central offices of 5G architecture and hence various deployment options. Network function virtualization allocates radio access network (RAN) functions in different nodes. URLLC services require function placement nearer to the ran to fulfill the lower latency requirement while eMBB require cloud access for implementation. Therefore arbitrary allocation of network function for different services is not possible. We aim to developed algorithms to find service-based placement for RAN functions in a multitenant environment with heterogeneous demands. We considered three generic classes of slices of eMBB, URLLC, mMTC. Every slice is characterized by some specific requirements, while the nodes and the links are resources constrained. The function placement problem corresponds to minimize the overall cost of allocating the different functions to the different nodes organized in layers for respecting the requirements of the given slices. Specifically, we proposed three algorithms based on the normalized preference associated with each slice on different layers of RAN architecture. The maximum preference algorithm places the functions on the most preferred position defined in the preference matrix. On the other hand, the proposed modified preference algorithm provides solutions by keeping track of the availability of computational resources and latency requirements of different services. We also used the Exhaustive Search Method for solving a function allocation problem.