A Petri Net-based model to Study the Impact of Traffic Changes on 5G Network Resilience

Abstract

The advent of 5G has enabled a wide variety of devices to access the network. With the digitization of industry, more and more vertical services, such as smart cities, remote health, and autonomous driving, rely on 5G networks for communication. These verticals bring new challenges to the telecommunication network resilience. Among them, sudden traffic change seems to be a critical challenge that impacts the resilience performance of 5G networks. This paper presents a network model for future 5G infrastructures based on Petri nets by taking into consideration the particularities of network virtualization and softwarization. This work also seeks to analyze the effectiveness of microservice-level autoscaling and network isolation by using discrete event simulation. The results suggest that both autoscaling and network isolation could increase network resilience when network traffic changes abruptly.