The Emerging Role of Digital Twin Technologies in Computer Engineering Research: A Systematic Literature Review

Abstract

Digital twin technology is emerging as a key enabler of cyber-physical systems, intelligent networks, and data-driven automation, yet research on digital twins is often framed from mechanical or electrical perspectives rather than from computer engineering. While several comprehensive surveys have addressed digital twin enabling technologies (Mihai et al., 2022), security threats (Alcaraz & Lopez, 2022), industrial IoT applications (Xu et al., 2023), and business innovation perspectives (Lim et al., 2020), none of these reviews systematically examines how core computer engineering concerns, including embedded platforms, hardware-software co-design, real-time scheduling, edge-cloud orchestration, and on-device AI, collectively shape the design, deployment, and evaluation of digital twin systems. This paper addresses that gap through a systematic literature review of 45 peer-reviewed publications, conducted using the PRISMA 2020 framework, that explicitly engage with digital twins in computer engineering contexts. Using inductive thematic analysis, these studies were classified into six themes: (i) computer engineering foundations of digital twin systems, including embedded and real-time platforms, hardware-software co-design, and cyber-physical architectures; (ii) networked and distributed infrastructure for digital twins, including IoT, 5G/6G, and edge-cloud computing; (iii) computer engineering for intelligent digital twins, including on-device AI, learning-enabled control, and integration of machine learning with twin models; (iv) security, privacy, and dependability in digital twin-enabled cyber-physical systems; (v) modeling, simulation, and testing of digital twin systems; and (vi) application domains and use cases. Unlike prior surveys that catalog digital twin technologies by domain or threat model, this review synthesizes findings through a computer engineering lens, revealing that (i) networked and AI-enabled twins are growing rapidly but remain largely at the prototype stage, (ii) few studies rigorously evaluate digital twin implementations on constrained computing platforms, and (iii) interoperability, standardized validation, and safe adaptivity remain critical open problems. The paper concludes with a research agenda for hardware-aware, security-integrated, and systematically validated digital twin design in computer engineering.