Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

Springer Nature Link
Log in

A model framework-based domain-specific composable modeling method for combat system effectiveness simulation

  • Regular Paper
  • Published:
Software & Systems Modeling Aims and scope Submit manuscript

Abstract

Combat system effectiveness simulation (CoSES) plays an irreplaceable role in the effectiveness measurement of combat systems. According to decades of research and practice, composable modeling and multi-domain modeling are recognized as two major modeling requirements in CoSES. Current effectiveness simulation researches attempt to cope with the structural and behavioral complexity of CoSES based on a unified technological space, and they are limited to their existing modeling paradigms and fail to meet these two requirements. In this work, we propose a model framework-based domain-specific composable modeling method to solve this problem. This method builds a common model framework using application invariant knowledge for CoSES, and designs domain-specific modeling infrastructures for subdomains as corresponding extension points of the framework to support the modeling of application variant knowledge. Therefore, this method supports domain-specific modeling in multiple subdomains and the composition of subsystem models across different subdomains based on the model framework. The case study shows that this method raises the modeling abstraction level, supports generative modeling, and promotes model reuse and composability.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Zimmerman, P.: DoD Modeling and Simulation Support to Acquisition. NDIA Modeling & Simulation Committee, February 21 (2013)

  2. Davis, P.K., Bigelow, J.H.: Experiments in Multiresolution Modeling. RAND Corporation, Santa Monica, CA (1998)

    Google Scholar 

  3. Modarres, M., Cheon, S.W.: Function-centered modeling of engineering systems using the goal tree—success tree technique and functional primitives. Reliab. Eng. Syst. Saf. 64(2), 181–200 (1999)

    Article  Google Scholar 

  4. Li, X., Lei, Y., Wang, W., Wang, W., Zhu, Y.: A DSM-based multi-paradigm simulation modeling approach for complex systems. In: Winter Simulation Conference, pp. 1179–1190 (2013)

  5. Li, X., Lei, Y., Vangheluwe, H., Wang, W., Li, Q.: A multi-paradigm decision modeling framework for combat system effectiveness measurement based on domain-specific modeling. J. Zhejiang Univ. C 14(5), 311–331 (2013)

    Article  Google Scholar 

  6. Li, X., Lei, Y., Vangheluwe, H., Wang, W., Li, Q.: Domain specific decision modelling and statistical analysis for combat system effectiveness simulation. J. Stat. Comput. Simul. 84(6), 1261–1279 (2014)

    Article  MathSciNet  Google Scholar 

  7. Balci, O.: A life cycle for modeling and simulation. Simul. Trans. Soc. Model. Simul. Int. 88(7), 870–883 (2012)

    Google Scholar 

  8. Sarjoughian, H., Zeigler, B.: DEVS and HLA: Complementary paradigms for modeling and simulation? Simul. Trans. Soc. Model. Simul. Int. 17(4), 187–197 (2000)

    Google Scholar 

  9. Zeigler, B.P., Praehofer, H., Kim, T.G.: Theory of Modeling and Simulation: Integrating Discrete Event and Continuous Complex Dynamic Systems, 2nd edn. Academic Press, New York (2000)

    Google Scholar 

  10. Modelica Association: Modelica—A Unified Object-Oriented Language for Systems Modeling Language Specification Version 3.3 (2010). http://www.modelica.org/. Accessed 30 Apr 2013

  11. Hall, S.B., Zeigler, B.P., Sarjoughian, H.S.: JointMEASURE: distributed simulation issues in a mission effectiveness analytic simulator. In: Proceedings of the Simulation Interoperability Workshop (1999)

  12. Kwon, S.J., Seo, K., Kim, B., Kim, T.G.: Effectiveness analysis of anti-torpedo warfare simulation for evaluating mix strategies of decoys and jammers. In: Proceedings in Information and Communications Technology, pp. 385–393 (2012)

  13. SISO Base Object Model Product Development Group: Base Object Model (BOM) Template Specification (2006)

  14. European Space Agency: SMP 2.0 Handbook (Issue 1 Revision 2) EGOS-SIM-GEN-TN-0099 (2005)

  15. IEEE-SA Standards Board: IEEE Std 1516-2000: IEEE standard for modeling and simulation (M&S) high level architecture (HLA)—framework and rules (2000)

  16. US Army Space and Missile Defense Command, EADSIM Executive Summary (2013). www.eadsim.com/EADSIMExecSum.pdf/. Accessed 28 Apr 2013

  17. JMASS Overview. https://www.jmass.wpafb.af.mil. Accessed 25 Apr 2013

  18. IEEE-SA Standards Board: IEEE Standard for Modeling and Simulation High Level Architecture—Federate Interface Specification. IEEE (2010)

  19. Zacharewicz, G., Frydman, C., Giambiasi, N.: G-DEVS/HLA environment for distributed simulations of workflows. Simulation 84(5), 197–213 (2008)

    Article  Google Scholar 

  20. France, R., Rumpe, B.: Domain specific modeling. Softw. Syst. Model. 4(1), 1–3 (2005)

    Article  Google Scholar 

  21. Kelly, S., Tolvanen, J.: Domain Specific Modeling: Enabling Full Code Generation, p. 437. Wiley-IEEE Computer Society Press, Hoboken (2008)

    Book  Google Scholar 

  22. Li, X., Lei, Y., Vangheluwe, H., Wang, W., Li, Q.: Towards a DSM-based framework for the development of complex simulation systems. In: Summer Computer Simulation Conference, pp. 210–215 (2011)

  23. Vallecillo, A.: On the combination of domain specific modeling languages. Eur. Conf. Model. Found. Appl. 6138, 305–320 (2010)

    Article  Google Scholar 

  24. Lochmann, H., Hessellund, A.: An integrated view on modeling with multiple domain-specific languages. In: Proceedings of the IASTED International Conference Software Engineering, pp. 1–10 (2009)

  25. Alberts, D.S., Garstka, J.J., Stein, F.P.: Network Centric Warfare: Developing and Leveraging Information Superiority (2000)

  26. Yang, F., Wang, W., Lei, Y.: Equipment Combat Effectiveness Simulation and Evaluation, 1st edn. Publishing House of Electronics Industry, Beijing (2010). (in Chinese)

    Google Scholar 

  27. Li, C.: UML-Based SMP2 Model Design and Integration. National University of Defense Technology (in Chinese) (2009)

  28. Harel, D.: Statecharts: A visual formalism for complex systems. Sci. Comput. Program. 8(3), 231–274 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  29. Modelica Association: Modelica—A Unified Object-Oriented Language for Systems Modeling Language Specification Version 3.2 (2010)

  30. Denckla, B., Mosterman, P.J.: Formalizing Causal Block Diagrams for Modeling a Class of Hybrid Dynamic Systems. In: Proceedings of the 44th IEEE Conference Decision and Control, pp. 4193–4198 (2005)

  31. Clark, T., Evans, A., Kent, S.: Engineering Modelling Languages: A Precise Meta-Modelling Approach Lect. Notes Comput. Sci. Fundam. Approaches to. Softw. Eng. 2306, 159–173 (2002)

    Google Scholar 

  32. Atkinson, C., Kühne, T.: Model-driven development—a metamodeling foundation. IEEE Softw. 20(5), 36–41 (2003)

    Article  Google Scholar 

  33. Vangheluwe, H., Sun, X., Bodden, E.: Domain-specific modelling with AToM3. In: Second International Conference on Software and Data Technologies (2007)

  34. de Lara, J., Vangheluwe, H.: AToM3: A tool for multi-formalism and meta-modelling In: In European Joint Conference on Theory and Practice of Software (ETAPS), Fundamental Approaches to Software, pp. 174–188 (2002)

  35. Vanderbilt University, GME Manual and User Guide- Generic Modeling Environment 10 (2010)

  36. Tolk, A., Muguira, J.A.: The Levels of Conceptual Interoperability Model. In: 2003 Fall Simulation Interoperability Workshop, September (2003)

  37. Sprinkle, J., Rumpe, B., Vangheluwe, H., Karsai, G.: Metamodelling: State of the Art and Research Challenges. In: Giese, H., Karsai, G., Lee, E.A., Rumpe, B., Schätz, B. (eds.) Model-Based Engineering of Embedded. Real-Time Systems, vol. 6100, pp. 57–76 (2010)

  38. Emerson, M.J., Sztipanovits, J.: Implementing a MOF-Based Metamodeling Environment Using Graph Transformations In: 4th OOPSLA workshop on domain-specific modeling, pp. 83–92 (2004)

  39. Chen, K., Sztipanovits, J., Neema, S.: Toward a Semantic Anchoring Infrastructure for Domain-Specific Modeling Languages. In: Fifth ACM International Conference on Embedded Software, pp. 35–43 (2005)

  40. Balasubramanian, D., Narayanan, A., VanBuskirk, C., Karsai, G.: The graph rewriting and transformation language: GReAT. In: Third International Workshop on Graph Based Tools, vol. 1, pp. 1–8 (2006)

Download references

Acknowledgments

We specially thank the anonymous reviewers for their valuable suggestions and advices which greatly improve the quality of this paper. We thank our colleagues, Professor Qun Li and Dr. Chao Wang, for their contributions on SMP2 simulation system implementation. We are grateful to the suggestions and insights provided by Professor Hans Vangheluwe from University of Antwerp and Professor Pieter Mosterman from McGill University. The work presented in this paper is partly supported by the National Natural Science Foundation of China (Nos. 61273198 and 71401167).

Author information

Authors and Affiliations

  1. College of Information Systems and Management, National University of Defense Technology, Changsha, 410073, Hunan, People’s Republic of China

    Xiao-bo Li, Feng Yang, Yong-lin Lei, Wei-ping Wang & Yi-fan Zhu

  2. Department of Mathematics and Computer Science, University of Antwerp, 2020, Antwerp, Belgium

    Xiao-bo Li

Authors
  1. Xiao-bo Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Feng Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yong-lin Lei
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wei-ping Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yi-fan Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Feng Yang.

Additional information

Communicated by Dr. Sebastien Gerard.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Xb., Yang, F., Lei, Yl. et al. A model framework-based domain-specific composable modeling method for combat system effectiveness simulation. Softw Syst Model 16, 1201–1222 (2017). https://doi.org/10.1007/s10270-015-0513-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10270-015-0513-x

Keywords

Search

Navigation