Industrial Cyber-Physical Systems (CPS) drive industry sectors worldwide, combining physical and software components into sophisticated interconnected systems. Distributed CPS (dCPS) further enhance these systems by interconnecting multiple distributed subsystems through intricate, complex networks. Researchers and industrial designers need to carefully consider various design options that have the potential to impact system behaviour, cost, and performance during the development of dCPS. However, the increased size and complexity present manufacturing companies with new challenges when designing their next-generation machines. Furthermore, objectively evaluating these ma-chines' vast number of potential arrangements can be resource-intensive. One of the approaches designers can utilise to aid themselves with early directions in the design process is Design Space Exploration (DSE). Nevertheless, the vast amount of potential design points (a single system configuration) in the design space (collection of all possible design points) poses a significant challenge to scalably and efficiently reach an exact or reasonable solution during the design process.
This thesis addresses the scalability challenge in the design process employed by researchers and designers of the next-generation complex dCPS. A baseline of understanding is constructed of the state-of-the-art, its complexity, research directions, and challenges in the context of DSE for dCPS and related research fields. To facilitate scalable and efficient DSE for dCPS, an evaluation environment is proposed, implemented, and evaluated. The research considers key design considerations for developing a distributed evaluation workflow that can dynamically be adapted to enable efficient and scalable exploration of the vast design space of complex, distributed Cyber-Physical Systems. Evaluation of the proposed environment employs a set of system models, representing design points within a DSE process, to assess the solution and its behaviour, performance, capability, and applicability in addressing the scalability challenge in the context of DSE for dCPS. During the evaluation, the performance and behaviour are investigated in three areas: (i) Simulation Campaign , (ii) Task Management Configuration, and (iii) Parallel Discrete-Event Simulation (PDES). Throughout the evaluation, it is demonstrated that the proposed environment is capable of providing scalable and efficient evaluation of design points in the context of DSE for dCPS. Furthermore, the proposed solution enables designers and researchers to tailor it to their environment through dynamic complex workflows and interactions, workload-level and task-level parallelism, and simulator and compute environment agnosticism.
The outcomes of this research contribute to advancing the research field towards scalable and efficient evaluation for DSE of dCPS, supporting designers and researchers developing their next-generation dCPS. Nevertheless, further research can be conducted on the impact of a system's behavioural characteristics on the performance and behaviour of the proposed solution when using the PDES methodology. Additionally, the interaction between external applications and the proposed solution could be investigated to support and enable further complex interactions and requirements.