Information schema constructs for instantiation and composition of system manifestation features
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Complementing our previous publications, this paper presents the information schema constructs (ISCs) that underpin the programming of specific system manifestation feature (SMF) orientated information management and composing system models. First, we briefly present (1) the general process of pre-embodiment design with SMFs, (2) the procedures of creating genotypes and phenotypes of SMFs, (3) the specific procedure of instantiation of phenotypes of SMFs, and (4) the procedure of system model management and processing. Then, the chunks of information needed for instantiation of phenotypes of SMFs are discussed, and the ISCs designed for instantiation presented. Afterwards, the information management aspects of system modeling are addressed. Methodologically, system modeling involves (1) placement of phenotypes of SMF in the modeling space, (2) combining them towards the desired architecture and operation, (3) assigning values to the parameters and checking the satisfaction of constraints, and (4) storing the system model in the SMFs-based warehouse database. The final objective of the reported research is to develop an SMFs-based toolbox to support modeling of cyber-physical systems (CPSs).
Key wordsSystem manifestation features (SMFs) Information schema constructs Database schemata SMF genotypes SMF phenotypes SMF instances Software tool box System-level design Cyber-physical systems
CLC numberTP391 TP311
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- Bhave, A., Krogh, B., Garlan, D., et al., 2010. Multi-domain modeling of cyber-physical systems using architectural views. Proc. Analytic Virtual Integration of Cyber- Physical Systems Workshop.Google Scholar
- Frevert, R., Haase, J., Jancke, R., et al., 2005. System level modeling. In: Modeling and Simulation for RF System Design. Springer, Boston, MA, p.25–38. https://doi.org/10.1007/0-387-27585-1_4Google Scholar
- Hadorn, B., Courant, M., Hirsbrunner, B., 2015. Holistic system modelling for cyber physical systems. Proc. 6th Int. Multi-conf. on Complexity, Informatics and Cybernetics.Google Scholar
- Horváth, I., Pourtalebi, S., 2015. Fundamentals of a Mereo-Operandi theory to support transdisciplinary modeling and co-design of cyber-physical systems. Proc. ASME Int. Design Engineering Technical Conf., p.1–12. https://doi.org/10.1115/DETC2015-46702Google Scholar
- Macal, M.C., North, J.M., 2006a. Tutorial on agent-based modeling and simulation. Part 2: how to model with agents. Proc. 38th Winter Simulation Conf., p.73–83.Google Scholar
- Munir, S., Ahmed, M., Stankovic, J., 2015. EyePhy: detecting dependencies in cyber-physical system Apps due to human- in-the-loop. Proc. 12th EAI Int. Conf. on Mobile and Ubiquitous Systems: Computing, Networking and Services, p.170–179. https://doi.org/10.4108/eai.22-7-2015.2260045Google Scholar
- Pourtalebi, S., Horváth, I., 2016b. Procedures for creating system manifestation features: an information processing perspective. Proc. Int. Symp. on Tools and Methods of Competitive Engineering, p.1–16.Google Scholar
- Zhou, K.L., Liu, B.B., Ye, C., et al., 2013. Design support tools of cyber-physical systems. In: Leung, V., Chen, M. (Eds.), Cloud Computing. Springer, Cham, p.258–267. https://doi.org/10.1007/978-3-319-05506-0_25Google Scholar