Information schema constructs for instantiation and composition of system manifestation features

  • Shahab PourtalebiEmail author
  • Imre Horváth


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 words

System manifestation features (SMFs) Information schema constructs Database schemata SMF genotypes SMF phenotypes SMF instances Software tool box System-level design Cyber-physical systems 

CLC number

TP391 TP311 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 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
  2. Broman, D., Lee, E.A., Tripakis, S., et al., 2012. Viewpoints, formalisms, languages, and tools for cyber-physical systems. Proc. ACM 6th Int. Workshop on Multi-paradigm Modeling, p.49–54. Scholar
  3. Derler, P., Lee, E.A., Vincentelli, A.S., 2012. Modeling cyber–physical systems. Proc. IEEE, 100(1):13–28. Scholar
  4. Edwards, J.R., Bagozzi, R.P., 2000. On the nature and direction of relationships between constructs and measures. Psychol. Methods, 5(2):155–174. Scholar
  5. Erbas, C., Pimentel, A.D., Thompson, M., et al., 2007. A framework for system-level modeling and simulation of embedded systems architectures. EURASIP J. Embed. Syst., 2007(1):082123. Scholar
  6. 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. Scholar
  7. Gavrilescu, M., Magureanu, G., Pescaru, D., et al., 2010. Accurate modeling of physical time in asynchronous embedded sensing networks. Proc. IEEE 8th Int. Symp. on Intelligent Systems and Informatics, p.477–482. Scholar
  8. 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
  9. 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. Scholar
  10. Lee, E.A., 2015. The past, present and future of cyber-physical systems: a focus on models. Sensors, 15:4837–4869. Scholar
  11. Lee, G., Sacks, R., Eastman, C., 2007. Product data modeling using GTPPM: a case study. Autom. Constr., 16(3):392–407. Scholar
  12. 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
  13. 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. Scholar
  14. Petnga, L., Austin, M., 2016. An ontological framework for knowledge modeling and decision support in cyberphysical systems. Adv. Eng. Inform., 30(1):77–94. Scholar
  15. Pourtalebi, S., Horváth, I., 2016a. Towards a methodology of system manifestation features-based pre-embodiment design. J. Eng. Des., 27(16):232–268. Scholar
  16. 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
  17. Pourtalebi, S., Horváth, I., 2016c. Information schema constructs for defining warehouse databases of genotypes and phenotypes of system manifestation features. Front. Inform. Technol. Electron. Eng., 17(9):861–884. Scholar
  18. Richter, G., 1981. Utilization of data access and manipulation in conceptual schema definitions. Inform. Syst., 6(1):53–71. Scholar
  19. Seiger, R., Keller, C., Niebling, F., et al., 2014. Modelling complex and flexible processes for smart cyber-physical environments. J. Comput. Sci., 10:137–148. Scholar
  20. Simko, G., Levendovszky, T., Maroti, M., et al., 2014. Towards a theory for cyber-physical systems modeling. Proc. 4th ACM SIGBED Int. Workshop on Design, Modeling, and Evaluation of Cyber-Physical Systems, p.56–61. Scholar
  21. 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. Scholar

Copyright information

© Zhejiang University and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Faculty of Industrial Design EngineeringDelft University of TechnologyZuid Hollandthe Netherlands

Personalised recommendations