End-to-End Mobile Network Slice Embedding Leveraging Edge Computing

Abstract

Network virtualization and network slicing are key-features of the fifth generation (5G) of mobile networks to overcome the challenge of increasingly diverging network requirements emerging from new use-cases like IoT, autonomous driving and Industry 4.0. In particular, low latency network slices require deployment of their services and applications, including Network Functions (NFs), close to the user, i.e., at the edge of the mobile network. Since the users of those services might be widely distributed and mobile, multiple instances of the same application are required to be available on numerous distributed edge clouds. This paper tackles the problem of Network Slice Embedding (NSE) with edge computing. Based on an Integer Linear Program (ILP) formulation of the NSE problem, the optimal set of network slices, in terms of network slice revenue and cost, is determined. The required network slice applications, functions and services are allocated nearly optimally on the 5G end-to-end mobile network infrastructure. The presented solution also provides the optimal number of application instances and their optimal deployment locations on the edge clouds, even for multiple User Equipment (UE) connectivity scenarios. Evaluation shows that the proposed holistic approach for NSE and multiple edge cloud allocation is feasible and efficient for small and medium sized problem instances.