[Paper Review] The Paradigm of Digital Twin Communications

Tom H. Luan, Ruhan Liu+3 more|arXiv (Cornell University)|May 15, 2021

Digital Transformation in Industry12 references37 citations

TL;DR

This paper introduces the concept of digital twin (DT) communications, outlining a four-part DT model (PE, DR, intra-twin, inter-twin) and exploring deployment, comparison with cloud/edge/Mobile Cloud, and open research issues.

ABSTRACT

With the fast evolving of cloud computing and artificial intelligence (AI), the concept of digital twin (DT) has recently been proposed and finds broad applications in industrial Internet, IoT, smart city, etc. The DT builds a mirror integrated multi-physics of the physical system in the digital space. By doing so, the DT can utilize the rich computing power and AI at the cloud to operate on the mirror physical system, and accordingly provides feedbacks to help the real-world physical system in their practical task completion. The existing literature mainly considers DT as a simulation/emulation approach, whereas the communication framework for DT has not been clearly defined and discussed. In this article, we describe the basic DT communication models and present the open research issues. By combining wireless communications, artificial intelligence (AI) and cloud computing, we show that the DT communication provides a novel framework for futuristic mobile agent systems.

Motivation & Objective

• Motivate the DT concept as a communication framework bridging cloud/AI with mobile agents.
• Describe the DT structure (PE, DR, intra-twin, inter-twin) and private synchronization needs.
• Discuss deployment strategies (cloud, edge, PE trust zone) and how DRs differ from traditional cloud/edge roles.
• Compare DT to cloud, edge, mobile cloud, and AI paradigms to justify its unique benefits.
• Identify open research issues in intra-twin and inter-twin communications for future work.

Proposed method

• Define the DT communication model with four components: PE, DR, intra-twin, inter-twin.
• Explain DR characteristics: always-on, synchronization, private, autonomous.
• Survey three deployment scenarios (cloud, edge, PE trust zone) and discuss privacy and synchronization implications.
• Compare DT with cloud computing, edge computing, mobile cloud computing, and AI methods.
• Outline open research issues in intra-twin and inter-twin communication efficiency and security.

Experimental results

Research questions

• RQ1 What is the basic structure of a digital twin communication system and how do its components interact?
• RQ2 How should DRs be deployed, and what are the privacy and synchronization requirements?
• RQ3 How does DT compare to cloud/edge/mobile cloud computing and AI in enabling mobile agent systems?
• RQ4 What are the key open research challenges in intra-twin and inter-twin communications?

Key findings

• DT provides a private, synchronized intra-twin link between PE and DR for secure data sharing.
• DRs enable autonomous, cloud-assisted task execution and bidirectional synchronization with PEs.
• Inter-twin communications involve DR-to-DR data sharing with permission checks and potential blockchain-based integrity.
• DT deployment choices (cloud/edge/PE) each offer privacy, latency, and mobility trade-offs.
• Compared to cloud/edge/mobile cloud, DT positions DR as a private software entity with one-to-one mapping to PE and proactive capabilities.
• Identifies security, data location, and privacy considerations as central open issues for both intra-twin and inter-twin communications.