TOPSIS‐based approach for network slice selection in 5G mobile systems

Abstract

SummaryFifth‐generation (5G) mobile networks can be perceived as highly manageable systems that provide increased performance while supporting a variety of services with widely diverse requirements. Recently, network slicing has been proposed by academia and industry as a resource provisioning technique capable to meet these requirements with reduced operating costs while opening new horizons for network efficiency. The aim of network slice selection function (NSSF) is an optimal selection of network instances serving the users, based on local configuration, and other available information including radio access networks (RANs) performances in the registration area. In this paper, NSSF based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is proposed. Here, the network slices are treated as alternatives while their performance indicators are considered as the criteria for decision making. The influences of various alternative techniques, taking into account all the three stages of decision making process, that is, normalization, weighting, and ranking, are analyzed through the rank reversal phenomenon and computational complexity. Simulation results reveal that the proposed techniques can significantly improve the network slice selection procedure.