Toward Digital Twin-as-a-Service (DTaaS) Platforms: A Survey on Architecture, Design Requirements, and Performance Metrics

Digital Twin-as-a-Service (DTaaS) has emerged as a transformative paradigm to deliver modular, scalable, and intelligent digital twin (DT) functionalities. Regarding this, several studies have investigated DT platforms and their enabling technologies. However, their focus mostly remains domain-specific, thereby limiting the potential for generalisation across diverse contexts. Furthermore, these studies lack a systematic framework to address both architectural elements and their performance evaluation required for an end-to-end DTaaS platform. To bridge this gap, in this survey, we present a comprehensive component-based taxonomy for DTaaS platforms, categorised into <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">core</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">supportive</i> components. As the core components, we review Data, Model, Service, and Communication, whereas the supportive components include Infrastructure, Orchestration, and Security elements. For each component, we analyse the state-of-the-art methods, enabling technologies, and associated design trade-offs. We further introduce a metric-driven perspective to design measurable and context-aware DTaaS platforms. In this regard, we present several DT performance metrics, including twinning rate, twin fidelity, and age-of-twin and map them to DTaaS components. To demonstrate the applicability of our framework, we present a case study based on our own DTaaS platform. We perform two metric-driven implementations, (i) Radio Access Network (RAN) management and (ii) Distributed Denial of Service (DDoS) attack detection by exemplifying how DT-metrics can be integrated with the DTaaS components. Also, we outline key open issues for context-aware, interoperable, and secure DTaaS platforms. By jointly addressing an end-to-end architectural design and performance metrics, this survey demonstrates a foundational reference for the structured development, evaluation, and operation of DTaaS platforms.