  5G radio access network (RAN) with network slicing methodology plays a key
role in the development of the next-generation network system. RAN slicing
focuses on splitting the substrate's resources into a set of self-contained
programmable RAN slices. Leveraged by network function virtualization (NFV), a
RAN slice is constituted by various virtual network functions (VNFs) and
virtual links that are embedded as instances on substrate nodes. In this work,
we focus on the following fundamental tasks: i) establishing the theoretical
foundation for constructing a VNF mapping plan for RAN slice recovery
optimization and ii) developing algorithms needed to map/embed VNFs
efficiently. In particular, we propose four efficient algorithms, including
Resource-based Algorithm (RBA), Connectivity-based Algorithm (CBA), Group-based
Algorithm (GBA), and Group-Connectivity-based Algorithm (GCBA) to solve the
resource allocation and VNF mapping problem. Extensive experiments are also
conducted to validate the robustness of RAN slicing via the proposed
algorithms.
