Performance Evaluation and Threat Mitigation in Large-scale 5G Core Deployment

TL;DR

This paper investigates the impact of DDoS-induced chaotic workloads on 5G core network performance, emphasizing resource diversity for SLA adherence and proposing kernel-based monitoring for scalable security in large-scale deployments.

Contribution

It provides empirical insights into managing DDoS effects, highlights the importance of diverse resource profiles, and demonstrates kernel-based monitoring for security in 5G core networks.

Findings

DDoS workloads significantly affect user registration performance.

Diverse resource profiles are essential for SLA compliance.

Kernel-based monitoring enhances security threat detection.

Abstract

The deployment of large-scale software-based 5G core functions presents significant challenges due to their reliance on optimized and intelligent resource provisioning for their services. Many studies have focused on analyzing the impact of resource allocation for complex deployments using mathematical models, queue theories, or even Artificial Intelligence (AI). This paper elucidates the effects of chaotic workloads, generated by Distributed Denial of Service (DDoS) on different Network Functions (NFs) on User Equipment registration performance. Our findings highlight the necessity of diverse resource profiles to ensure Service-Level Agreement (SLA) compliance in large-scale 5G core deployments. Additionally, our analysis of packet capture approaches demonstrates the potential of kernel-based monitoring for scalable security threat defense. Finally, our empirical evaluation provides insights into the effective deployment of 5G NFs in complex scenarios.