The emerging role of digital twin technologies in computer engineering research: a systematic literature review

Introduction Digital twin technology is emerging as a key enabler of cyber-physical systems, intelligent networks, and data-driven automation. However, research on digital twins is often framed from mechanical or electrical perspectives rather than from computer engineering. Although several comprehensive surveys have addressed enabling technologies, security threats, industrial IoT applications, and business innovation perspectives, none have systematically examined 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. Methods To address this gap, this paper presents a systematic literature review of 45 peer-reviewed publications that explicitly engage with digital twins in computer engineering contexts. The review was conducted using the PRISMA 2020 framework, and inductive thematic analysis was used to identify and synthesize major research themes across the selected studies. Results The analysis revealed six major 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. The review further shows that networked and AI-enabled digital twins are growing rapidly but remain largely at the prototype stage. Few studies rigorously evaluate digital twin implementations on constrained computing platforms, while interoperability, standardized validation, and safe adaptivity remain persistent challenges. Discussion and Conclusion Unlike prior surveys that catalog digital twin technologies by domain or threat model, this review synthesizes findings through a computer engineering lens. The results highlight the need for hardware-aware, security-integrated, and systematically validated approaches to digital twin design and deployment. The paper concludes by outlining a research agenda to advance the development of robust, interoperable, and scalable digital twin systems within computer engineering.