Transient Performance Modelling of 5G Slicing with Mixed Numerologies for Smart Grid Traffic

TL;DR

This paper models the transient performance of 5G network slicing with mixed numerologies for smart grid traffic, analyzing resource allocation and traffic interactions in heterogeneous 5G radio access networks.

Contribution

It introduces multi-dimensional Markov models to evaluate transient behaviors of 5G slicing with different numerologies for smart grid applications, considering traffic priority.

Findings

Traffic priority improves resource utilization.

Smart grid traffic impacts other session types.

Models predict transient performance under various scenarios.

Abstract

Network slicing enabled by fifth generation (5G) systems has the potential to satisfy diversified service requirements from different vertical industries. As a typical vertical industry, smart distribution grid poses new challenges to communication networks. This paper investigates the behavior of network slicing for smart grid applications in 5G radio access networks with heterogeneous traffic. To facilitate network slicing in such a network, we employ different 5G radio access numerologies for two traffic classes which have distinct radio resource and quality of service requirements. Three multi-dimensional Markov models are developed to assess the transient performance of network slicing for resource allocation with and without traffic priority. Through analysis and simulations, we investigate the effects of smart grid protection and control traffic on other types of parallel traffic sessions as well as on radio resource utilization.