The Interplay of AI and Digital Twin: Bridging the Gap between
Data-Driven and Model-Driven Approaches
- URL: http://arxiv.org/abs/2209.12423v2
- Date: Wed, 29 Mar 2023 13:00:07 GMT
- Title: The Interplay of AI and Digital Twin: Bridging the Gap between
Data-Driven and Model-Driven Approaches
- Authors: Lina Bariah and Merouane Debbah
- Abstract summary: The Digital Twin (DT) concept aims to create a virtual twin for the physical entities and network dynamics.
Despite the common understanding that AI is the seed for DT, we anticipate that the DT and AI will be enablers for each other.
- Score: 2.842794675894731
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The evolution of network virtualization and native artificial intelligence
(AI) paradigms have conceptualized the vision of future wireless networks as a
comprehensive entity operating in whole over a digital platform, with smart
interaction with the physical domain, paving the way for the blooming of the
Digital Twin (DT) concept. The recent interest in the DT networks is fueled by
the emergence of novel wireless technologies and use-cases, that exacerbate the
level of complexity to orchestrate the network and to manage its resources.
Driven by AI, the key principle of the DT is to create a virtual twin for the
physical entities and network dynamics, where the virtual twin will be
leveraged to generate synthetic data and offer an on-demand platform for AI
model training. Despite the common understanding that AI is the seed for DT, we
anticipate that the DT and AI will be enablers for each other, in a way that
overcome their limitations and complement each other benefits. In this article,
we dig into the fundamentals of DT, where we reveal the role of DT in unifying
model-driven and data-driven approaches, and explore the opportunities offered
by DT in order to achieve the optimistic vision of 6G networks. We further
unfold the essential role of the theoretical underpinnings in unlocking further
opportunities by AI, and hence, we unveil their pivotal impact on the
realization of reliable, efficient, and low-latency DT.
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