Dynamic Network Slicing Using Utility Algorithms and Stochastic Optimization

Abstract

Network slicing is a key enabler for next-generation 5G services. Slices are designed to offer different services by conjoining virtual network functions (VNFs) through a logical network. We propose a dynamic slicing algorithm, which is based on utility theory and facilitates the growth, provisioning, dimensioning and deletion of network slices. The proposed algorithm is based on a utility model that regulates the virtual topology of VNFs in data-centers. The algorithm optimizes the number of slices as well as instantiated VNFs, thereby creating/modifying and destroying network slices of appropriate granularity. In addition, we also propose a stochastic optimization formulation, which handles uncertainty in service requests. We simulate the algorithm for a multi-data-center model with a large set of slices. Our results indicate dynamism, robustness and scalability of the proposed algorithm.