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arXiv · 2207.07219

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

Ziran Min·Shashank Shekhar·Charif Mahmoudi·Valerio Formicola·Swapna Gokhale·Aniruddha Gokhale
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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.

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Ziran Min, Shashank Shekhar, Charif Mahmoudi, Valerio Formicola, Swapna Gokhale, Aniruddha Gokhale. 2022-07-14. Software-defined Dynamic 5G Network Slice Management for Industrial Internet of Things. https://arxiv.org/abs/2207.07219

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