한국시뮬레이션학회논문지 (Journal of the Korea Society for Simulation)

한국시뮬레이션학회 (The Korea Society for Simulation)
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사용자 수준 맞춤형 모델링 및 시뮬레이션을 위한 개발환경 및 확장된 DEVS 형식론

Development Environment and Extended DEVS Formalism for User-Level Customizable Modeling and Simulation

  • 투고 : 2018.08.03
  • 심사 : 2018.09.14
  • 발행 : 2018.09.30
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초록

복잡한 이산 사건 동적 시스템을 분석하기 위해 모델링 및 시뮬레이션(M&S) 기법을 적용함에 있어서, 기존에는 사용자 수준에 따라 각기 다른 시뮬레이션 환경을 사용해야 했다. 그에 따른 불편함을 해결하기 위하여 본 논문에서는 사용자 수준에 따라 M&S를 수행할 수 있는 통합된 개발 환경 및 개발 환경에서 모델을 효율적으로 관리하기 위해 정형화된 인터페이스를 제안한다. 인터페이스는 확장된 DEVS 형식론 및 모델 제작 규칙으로 구성되어있다. 개발 환경은 모델링 환경과 시뮬레이션 환경으로 나뉘고, 모델링 환경에서는 사용자의 수준별로 다른 모델링 방식을 제공한다. 모델링 작업의 결과로 생성된 모델을 활용하여 시뮬레이션 환경에서 여러 파라미터를 입력해서 시뮬레이션 함으로써 다양한 경우에 대해서 실험을 할 수 있다. 사례 연구에서는 제안한 M&S 환경을 구현한 내용에 대해 소개하고, 환경을 활용해서 복잡한 국방 전투 시스템을 모델링하고, 만들어진 모델을 바탕으로 시뮬레이션 하는 과정을 소개한다.

In applying modeling and simulation (M&S) techniques to analyze complex discrete event dynamic systems, conventionally users had to use different simulation environments depending on the user-level. To solve the inconvenience, this paper proposes an integrated development environment for M&S depending on user-level and a formalized interface to manage the model in the development environment efficiently. The interface consists of an extended DEVS formalism and model making rules. The development environment is divided into a modeling environment and a simulation environment. In the modeling environment, three modeling methods are provided for each level of the users. Users inputs several parameters to the model generated as a result of the modeling process, and experiments in various cases by using the simulation environment. The case study shows the implementation of the proposed M&S environment, and using the implemented environment, it shows the M&S process of the complex defense combat system.

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참고문헌

  1. Capocchi, Laurent, et al. (2011) "DEVSimPy: A collaborative python software for modeling and simulation of DEVS systems", 2011 20th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, IEEE, 170-175.
  2. Chidisiuc, Chiril, and Gabriel A. Wainer. (2007) "CD++ Builder: an eclipse-based IDE for DEVS modeling", Proceedings of the 2007 spring simulation multiconference-Volume 2, Society for Computer Simulation International, 235-240.
  3. Choi, Changbeom, Kyung-Min Seo, and Tag Gon Kim. (2014) "DEXSim: an experimental environment for distributed execution of replicated simulators using a concept of single simulation multiple scenarios." Simulation, 90(4), 355-376. https://doi.org/10.1177/0037549713520251
  4. Choi, Seon Han, and Tag Gon Kim. (2018) "Optimal subset Selection of stochastic model using statistical hypothesis test", IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(4), 557-564. https://doi.org/10.1109/TSMC.2016.2608982
  5. Bergero, Federico, and Ernesto Kofman. (2011) "Power DEVS: a tool for hybrid system modeling and realtime simulation.", Simulation, 87(1-2), 113-132. https://doi.org/10.1177/0037549710368029
  6. Borshchev, Andrei. (2013) The big book of simulation modeling: multimethod modeling with AnyLogic 6, Chicago: AnyLogic North America.
  7. Kelton, W. David. (2002) Simulation with ARENA, McGraw-hill.
  8. Kim, Tag Gon, et al. (2011) "DEVSim++ toolset for defense modeling and simulation and interoperation", The Journal of Defense Modeling and Simulation, 8(3), 129-142. https://doi.org/10.1177/1548512910389203
  9. Krahl, David. (2009) "ExtendSim advanced techology: discrete rate simulation.", Proceedings of Winter simulation conference, Winter Simulation Conference, 333-338.
  10. Lee, Jun Hee. (2018) "General-Purpose Discrete Event Modeling and Simulation Environment with User-Level Customizability", MS Thesis, KAIST.
  11. Lee, Loo Hay, et al. (2013) "Advances in simulation optimization and its applications", IIE Transactions, 45(7), 683-684. https://doi.org/10.1080/0740817X.2013.778709
  12. Matloff, Norm. (2008) "Introduction to discrete-event simulation and the simpy language." Davis, CA. Dept of Computer Science, University of California at Davis. Retrieved on August.
  13. Nordgren, William B. (2003) "Flexible simulation (Flexsim) software: Flexsim simulation environment", Proceedings of the 35th conference on Winter simulation: driving innovation, Winter Simulation Conference, 197-200.
  14. Sarjoughian, Hessam S., and Vignesh Elamvazhuthi. (2009) "CoSMoS: a visual environment for component-based modeling, experimental design, and simulation." Proceedings of the 2nd international conference on simulation tools and techniques, ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), 59.
  15. Seo, Kyung-Min, et al. (2011) "Measurement of Effectiveness for an Anti-torpedo Combat System Using a Discrete Event Systems Specificationbased Underwater Warfare Simulator", The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 8(3), 157-171. https://doi.org/10.1177/1548512910390245
  16. Zeigler, B. P., Kim. T. G., and Praehofer, H. (2000) Theory of Modeling and Simulation: Integrating Discrete Event and Continuous Complex Dynamic Systems, 2nd ed., San Diego, CA, USA: Academic Press.