Advertisement

To Execute the C4ISR Architecture Based on DoDAF and Simulink

  • Xiaokai Xia
  • Kaipeng Zhao
  • Luo Xu
  • Chao Liu
Part of the Communications in Computer and Information Science book series (CCIS, volume 402)

Abstract

In order to verify and evaluate the C4ISR systems before they are built, this paper proposes an approach to make the architecture developed by DoDAF executable. The model transformation technologies in model driven architecture are used to transform the architecture products, such as composite structure diagram, state machine diagram, activity diagram and sequence diagram, to single Simulink models and comprehensive Simulink models. The proposed approach can also effectively reuse the existing simulation blocks in the Simulink library to strengthen the ability of the generated Simulink model from architecture. Through the execution of the generated Simulink models, the data from the simulation can be used for the verificaiton and evaluation of the CRISR architecture. The case study shows the feasibility of the proposed approach.

Keywords

Executable C4ISR architecture DoDAF Simulink Model transformation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    DoD Architecture Framework Working Group: DoD architecture framework version 1.5, Volume I: Introduction. U.S. Department of Defense (2007)Google Scholar
  2. 2.
    Staines, T.S.: Intuitive mapping of UML 2 activity diagrams into fundamental modeling concept Petri net diagrams and colored Petri nets. In: 15th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems, pp. 191–200. Institute of Electrical and Electronics Engineers Inc., Belfast (2008)Google Scholar
  3. 3.
    Wang, R.Z., Dagli, C.H.: An Executable System Architecture Approach to Discrete Events System Modeling Using SysML in Conjunction with Colored Petri Net. In: 2nd Annual IEEE Systems Conference, pp. 1–8. IEEE Computer Society, Montreal (2008)Google Scholar
  4. 4.
    Ni, F., Wang, M.Z., Liao, J.J., Zhou, J.D.: Enhancing DoDAF with a HCPN executable model to support validation. In: 2th International Symposium on Computational Intelligence and Design, pp. 283–287. IEEE Press, Changsha (2009)Google Scholar
  5. 5.
    Wagenhals, L.W., Liles, S.W., Levis, A.H.: Toward executable architectures to support evaluation. In: 2009 International Symposium on Collaborative Technologies and Systems, pp. 502–511. IEEE Computer Society, Baltimore (2009)CrossRefGoogle Scholar
  6. 6.
    Bai, X.L., Luo, X.S., Bai, X.H., Chen, H.H., Guo, D.K.: Study of DoD architecture simulation validation based on UML and extended colored Petri nets. In: 2008 IEEE International Conference on Networking, Sensing and Control, pp. 61–66. IEEE Computer Society, Sanya (2008)Google Scholar
  7. 7.
    Raistrick, C., Francis, P., Wright, J.: Model driven architecture with executable UML. Cambridge University Press, New York (2006)Google Scholar
  8. 8.
    Ge, B.F., Ren, C.S., Zhao, Q.S., Yang, K.W., Chen, Y.W.: Executable architecture modeling and analysis for system of systems. Systems Engineering and Electronics 31, 2191–2201 (2011)Google Scholar
  9. 9.
    Griendling, K., Mavris, D.N.: Development of a DoDAF-based executable architecting approach to analyze system-of-systems alternatives. In: IEEE Aerospace Conference, pp. 1–15. IEEE press, Big Sky (2011)Google Scholar
  10. 10.
    Mittal, S.: Extending DoDAF to allow integrated DEVS based modeling and simulation. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 3, 95–123 (2006)CrossRefGoogle Scholar
  11. 11.
    Mittal, S., Mitra, A., Gupta, A., Zeigler, B.P.: Strengthening OV-6a semantics with rule-based meta-models in DEVS/DoDAF based life-cycle architectures development. In: 2006 IEEE International Conference on Information Reuse and Integration, pp. 80–85. IEEE Computer Society, Waikoloa Village (2006)CrossRefGoogle Scholar
  12. 12.
    Zeigler, B.P., Mittal, S.: Enhancing DoDAF with a DEVS-based system lifecycle development process. In: 2005 IEEE International Conference on Systems, Man and Cybernetics, pp. 3244–3251. IEEE, Waikoloa Village (2005)CrossRefGoogle Scholar
  13. 13.
    Helle, P.S., Giblett, I., Levier, P.: An integrated executable architecture framework for System of Systems development. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology (2013)Google Scholar
  14. 14.
    Garcia, J.J., Tolk, A.: Executable Architectures in Executable Context enabling Fit-for-Purpose and Portfolio Assessment. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology (2013)Google Scholar
  15. 15.
    Vanderperren, Y., Dehaene, W.: From UML/SysML to Matlab/Simulink: current state and future perspectives. In: DATE 2006 Proceedings of the Conference on Design, Automation and Test in Europe, p. 93. European Design and Automation Association, Belgium (2006)Google Scholar
  16. 16.
    Hooman, J., Mulyar, N., Posta, L.: Coupling Simulink and UML Models. In: Proc. Symposium FORMS/FORMATS (2004)Google Scholar
  17. 17.
    Brisolara, L., Oliveira, M., Nascimento, F.A., Carro, L., Wagner, F.R.: Using UML as a front-end for an efficient Simulink-based multithread code generation targeting MPSoCs. In: UML for SoC Design (UML-SoC 2007): 4th International UML DAC Workshop (2007)Google Scholar
  18. 18.
    Sjöstedt, C.J., Shi, J., Törngren, M., Servat, D., Chen, D., Ahlsten, V., Lönn, H.: Mapping Simulink to UML in the design of embedded systems: Investigating scenarios and transformations. In: OMER4 Workshop: 4th Workshop on Object-Oriented Modeling of Embedded Real-Time Systems (2007)Google Scholar
  19. 19.
    Boldt, R.: Combining the Power of MathWorks Simulink and Telelogic UML/SysML- based Rhapsody to Redefine the Model Driven Development Experience. Telelogic (2007)Google Scholar
  20. 20.
    Kai, X.X., Ji, W., Luo, X., Chao, L.: A Model-Driven Approach for Evaluating Systems of Systems. In: International Conference on Complex Computer Systems, Singapore (in press, 2013)Google Scholar
  21. 21.
    Jouault, F., Kurtev, I.: Transforming models with ATL. In: Bruel, J.-M. (ed.) MoDELS 2005. LNCS, vol. 3844, pp. 128–138. Springer, Heidelberg (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Xiaokai Xia
    • 1
  • Kaipeng Zhao
    • 1
  • Luo Xu
    • 1
  • Chao Liu
    • 1
  1. 1.School of Computer Science and EngineeringBeihang UniversityBeijingChina

Personalised recommendations