Empirical Application Insights on Industrial Data and Service Aspects of Digital Twin Networks

TL;DR

This paper investigates the practical application of digital twin networks in industrial environments, providing empirical insights, architectural frameworks, and exploring dual paradigms for improved resource management and service support.

Contribution

It offers empirical findings and a practical architectural extension of standards for applying DTNs in industrial networking, emphasizing dual paradigms of digital twins.

Findings

Empirical data on data fidelity and workload support in DTNs

An architectural framework extending ITU-T Y.3090 standards

Discussion of dual digital twin paradigms in industrial networks

Abstract

Digital twin networks (DTNs) serve as an emerging facilitator in the industrial networking sector, enabling the management of new classes of services, which require tailored support for improved resource utilization, low latencies and accurate data fidelity. In this paper, we explore the intersection between theoretical recommendations and practical implications of applying DTNs to industrial networked environments, sharing empirical findings and lessons learned from our ongoing work. To this end, we first provide experimental examples from selected aspects of data representations and fidelity, mixed-criticality workload support, and application-driven services. Then, we introduce an architectural framework for DTNs, exposing a more practical extension of existing standards; notably the ITU-T Y.3090 (2022) recommendation. Specifically, we explore and discuss the dual nature of DTNs, meant as a digital twin of the network and a network of digital twins, allowing the co-existence of both paradigms.