College
College of Engineering & Technology (Batten)
Department
Engineering Management and Systems Engineering
Graduate Level
Doctoral
Graduate Program/Concentration
Systems Engineering
Presentation Type
No Preference
Abstract
Organizations and industries increasingly rely on distributed services in decentralized environments—ranging from large-scale, system-of-system architectures to fine-grained, agent-based microservices. While this distributed paradigm offers flexibility and innovation, it presents critical challenges such as interoperability gaps, inconsistent data formats, and a lack of holistic oversight. Traditional integration approaches, including ad-hoc middleware or enterprise service buses, tend to solve these issues reactively. As a result, technical debt accumulates, stakeholder misalignments persist, and scaling to new demands becomes complex.
This research proposes digital thread (DT) as the unifying framework to create an authoritative source of truth: a continuous flow of information across the system lifecycle. Unlike data-centric solutions focusing on static datasets or one-off integrations, a process-oriented digital thread underscores the dynamic relationships, feedback loops, and evolving contexts in which services operate. DT weaves continuity, traceability, and interoperability—to provide a robust yet adaptable integration strategy. When applied to complex use cases—such as autonomous supply chain coordination, healthcare IoT infrastructures, or multi-agent transportation networks—this framework fosters real-time decision support and minimizes the risk of siloed operations. For instance, in a mobility-as-a-service platform comprising ride-sharing services (micro-level agents) and government-regulated transit systems (macro-level entities), a digital thread can reconcile data variety while ensuring regulatory compliance.
While the aerospace and automobile industry has demonstrated successful use cases of this approach, significant barriers like - integrating legacy infrastructure and scalability regarding security, privacy, and digital governance remain questionable. Remote deployment of services and cloud-based distribution also require elastic architectures and automated semantic reconciliation methods. Given these considerations, DT emerges as a transformative enabler in bridging macro to micro-level services. As industries increasingly turn to agent-based, distributed paradigms, the DT’s capacity to harmonize heterogeneity at scale positions it as a cornerstone for next-generation system integration and lifecycle management.
Keywords
System of Systems, Distributed Systems, Micro Services, Digital Twin, Digital Governance, Complex Systems Governance, Agentic Framework, Complexity, AI Agents
Included in
Artificial Intelligence and Robotics Commons, Computer and Systems Architecture Commons, Databases and Information Systems Commons, Industrial Engineering Commons, Other Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Architecture Commons, Systems Engineering Commons
Digital Thread: Bridging Macro–Micro Services in System-of-Systems
Organizations and industries increasingly rely on distributed services in decentralized environments—ranging from large-scale, system-of-system architectures to fine-grained, agent-based microservices. While this distributed paradigm offers flexibility and innovation, it presents critical challenges such as interoperability gaps, inconsistent data formats, and a lack of holistic oversight. Traditional integration approaches, including ad-hoc middleware or enterprise service buses, tend to solve these issues reactively. As a result, technical debt accumulates, stakeholder misalignments persist, and scaling to new demands becomes complex.
This research proposes digital thread (DT) as the unifying framework to create an authoritative source of truth: a continuous flow of information across the system lifecycle. Unlike data-centric solutions focusing on static datasets or one-off integrations, a process-oriented digital thread underscores the dynamic relationships, feedback loops, and evolving contexts in which services operate. DT weaves continuity, traceability, and interoperability—to provide a robust yet adaptable integration strategy. When applied to complex use cases—such as autonomous supply chain coordination, healthcare IoT infrastructures, or multi-agent transportation networks—this framework fosters real-time decision support and minimizes the risk of siloed operations. For instance, in a mobility-as-a-service platform comprising ride-sharing services (micro-level agents) and government-regulated transit systems (macro-level entities), a digital thread can reconcile data variety while ensuring regulatory compliance.
While the aerospace and automobile industry has demonstrated successful use cases of this approach, significant barriers like - integrating legacy infrastructure and scalability regarding security, privacy, and digital governance remain questionable. Remote deployment of services and cloud-based distribution also require elastic architectures and automated semantic reconciliation methods. Given these considerations, DT emerges as a transformative enabler in bridging macro to micro-level services. As industries increasingly turn to agent-based, distributed paradigms, the DT’s capacity to harmonize heterogeneity at scale positions it as a cornerstone for next-generation system integration and lifecycle management.