SYAIFeb 15, 2022

Towards Digital Twin Oriented Modelling of Complex Networked Systems and Their Dynamics: A Comprehensive Survey

arXiv:2202.09363v142 citations
Originality Synthesis-oriented
AI Analysis

It addresses the challenge of creating accurate Digital Twins for complex systems across disciplines, but it is incremental as it synthesizes existing work without introducing new methods.

This paper provides a comprehensive survey of modeling approaches for Complex Networked Systems (CNS) aimed at achieving Digital Twins (DTs), proposing a framework to compare and assess their capabilities and identifying future directions for integration.

This paper aims to provide a comprehensive critical overview on how entities and their interactions in Complex Networked Systems (CNS) are modelled across disciplines as they approach their ultimate goal of creating a Digital Twin (DT) that perfectly matches the reality. We propose a new framework to conceptually compare diverse existing modelling paradigms from different perspectives and create unified assessment criteria to assess their respective capabilities of reaching such an ultimate goal. Using the proposed criteria, we also appraise how far the reviewed current state-of-the-art approaches are from the idealised DTs. We also identify and propose potential directions and ways of building a DT-orientated CNS based on the convergence and integration of CNS and DT utilising a variety of cross-disciplinary techniques.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes