Software-defined Dynamic 5G Network Slice Management for Industrial Internet of Things

TL;DR

This paper introduces DANSM, a software-defined, autonomous network slice management middleware for 5G IIoT applications, which improves QoS, reduces response times, and enhances task completion efficiency.

Contribution

The paper presents DANSM, a novel software-defined middleware for dynamic 5G network slice management tailored for IIoT, demonstrating significant performance improvements.

Findings

DANSM reduces end-to-end response time in 5G IIoT networks.

DANSM completes 34% more subtasks than MGA.

DANSM minimizes operational costs while improving service performance.

Abstract

This paper addresses the challenges of delivering fine-grained Quality of Service (QoS) and communication determinism over 5G wireless networks for real-time and autonomous needs of Industrial Internet of Things (IIoT) applications while effectively sharing network resources. Specifically, this work presents DANSM, a software-defined, dynamic and autonomous network slice management middleware for 5G-based IIoT use cases, such as adaptive robotic repair. Empirical studies evaluating DANSM on our testbed comprising a Free5GC-based core and UERANSIM-based simulations reveal that the software-defined DANSM solution can efficiently balance the traffic load in the data plane thereby reducing the end-to-end response time and improve the service performance by completing 34% more subtasks than a Modified Greedy Algorithm (MGA), 64% more subtasks than First Fit Descending (FFD) and 22% more subtasks than Best Fit Descending (BFD) approaches all while minimizing operational costs.