정보과학회 논문지 (Journal of KIISE)

  • 제42권7호
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  • Pages.889-900
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  • 2015
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  • 2383-630X(pISSN)
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  • 2383-6296(eISSN)
한국정보과학회 (Korean Institute of Information Scientists and Engineers)
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확장된 동적 결정 네트워크기반 자가적응형 시스템

An Extended DDN based Self-Adaptive System

  • 김미수 (성균관대학교 전자전기컴퓨터공학과) ;
  • 정호현 (성균관대학교 전자전기컴퓨터공학과) ;
  • 이은석 (성균관대학교 전자전기컴퓨터공학과)
  • 투고 : 2015.03.17
  • 심사 : 2015.05.17
  • 발행 : 2015.07.15
⟨ 이전 논문 다음 논문 ⟩

초록

최근 복잡해진 시스템의 실행 환경에서 발생하는 문제들을 해결하기 위해 자가적응형 시스템의 중요성이 대두되고 있다. 그러나 시스템 설계 시점에 구축된 모델과 실행 환경 사이의 불확실성이 시스템을 알 수 없는 상황으로 이끌 수 있기 때문에 이를 다루기 위한 연구가 중요한 이슈로 떠오르고 있다. 본 논문은 불확실한 상황에서 적응 시점을 결정하고 모델에 실시간 환경을 반영하기 위한 방법을 제안한다. 적합한 적응 시점을 위해 시스템의 이전 상태들과 현재상태를 비교하여 베이지안 서프라이즈를 계산하고, 설계된 모델에 실시간 환경을 수행된 적응 정책의 결과를 모델에 반영한다. 제안 방법론을 네비게이션 시스템에 적용하여 제안 사항의 유효성을 확인하였다.

In order to solve problems happening in the practical environment of complicated system, the importance of the self-adaptive system has recently begun to emerge. However, since the differences between the model built at the time of system design and the practical environment can lead the system into unpredictable situations, the study into methods of dealing with it is also emerging as an important issue. In this paper, we propose a method for deciding on the adaptation time in an uncertain environment, and reflecting the real-time environment in the system's model. The proposed method calculates the Bayesian Surprise for the suitable adaptation time by comparing previous and current states, and then reflects the result following the performed policy in the design model to help in deciding the proper policy for the actual environment. The suggested method is applied to a navigation system to confirm its effectiveness.

키워드

과제정보

연구 과제 주관 기관 : 한국연구재단

참고문헌

  1. Salehie, Mazeiar, and Ladan Tahvildari, "Self-adaptive software: Landscape and research challenges," ACM Transactions on Autonomous and Adaptive Systems, Vol. 4, Issue. 2, No. 14. 2009.
  2. VAN Van Lamsweerde, Axel, "Goal-oriented requirements engineering: A guided tour," Proc. of the Fifth IEEE International Symposium on Requirements Engineering, pp. 249-262, 2001.
  3. Cheng, Betty HC, et al., "A goal-based modeling approach to develop requirements of an adaptive system with environmental uncertainty," Model Driven Engineering Languages and Systems, pp. 468-483, Springer Berlin Heidelberg, 2009.
  4. Chung, Lawrence, and Julio Cesar Sampaio do Prado Leite, "On non-functional requirements in software engineering," Conceptual modeling: Foundations and applications, pp. 363-379, Springer Berlin Heidelberg, 2009.
  5. Welsh, Kristopher, Pete Sawyer, and Nelly Bencomo, "Towards requirements aware system s: Runtime resolution of design-time assumptio ns," Proc. of the 26th IEEE /ACM International Conference on Automated Software Engineering, pp. 560-563, 2011.
  6. Bencomo, Nelly, and Amel Belaggoun, "Supporting decision-making for self-adaptive systems: from goal models to dynamic decision networks," Requirements Engineering: Foundation for Software Quality, pp. 221-236, Springer Berlin Heidelberg, 2013.
  7. Russell and Peter Norvig, "Artificial Intelligence: A modern approach," Prentice-Hall, Englewood Cliffs 25, 1995.
  8. Van Lamsweerde, Axel, and Emmanuel Letier. "From object orientation to goal orientation: A paradigm shift for requirements engineering," Radical Innovations of Software and Systems Engineering in the Future, pp. 325-340, Springer Berlin Heidelberg, 2004.
  9. Eric, S. Yu, "Social Modeling and i*," Conceptual Modeling: Foundations and Applications, pp. 99- 121, Springer Berlin Heidelberg, 2009.
  10. Morandini, Mirko, Loris Penserini, and Anna Perini, "Towards goal-oriented development of self-adaptive systems," Proc. of the international workshop on Software engineering for adaptive and selfmanaging systems, pp. 9-16, 2008.
  11. Baresi, Luciano, Liliana Pasquale, and Paola Spoletini, "Fuzzy goals for requirements-driven adaptation," Proc. of the Requirements Engineering Conference, pp. 125-134, 2010.
  12. M. Mitchell Waldrop, "Modeling Surprise," MIT Technology Review, 2008.
  13. Itti, Laurent, and Pierre Baldi, "Bayesian surprise attracts human attention," Vision research, Vol. 49, Issue. 10, pp. 1295-1306, 2009. https://doi.org/10.1016/j.visres.2008.09.007
  14. Kephart, J., et al., "An architectural blueprint for autonomic computing," IBM White Paper, 2003.
  15. Wong, Tzu-Tsung, "Generalized Dirichlet distribution in Bayesian analysis," Applied Math ematics and Computation, Vol. 97, Issue. 2-3, pp. 165-181, 1998. https://doi.org/10.1016/S0096-3003(97)10140-0
  16. Dasom, Hwang, et al., "A Study on dynamic weightchanging method of goal model for self-adaptive system," Proc. of the KIPS Fall Conference, pp. 1354- 1357. 2011. (in Korean)
  17. Jeong, Hohyeon, et al., "DSRC Based Self-Adaptive Navigation System: Aiming Spread Out the Vehicles for Alleviating Traffic Congestion," Frontier and Innovation in Future Computing and Communications, pp. 739-749, Springer Netherlands, 2014.
  18. SUMO, [Online]. Available: http://sumo.sourceforge.net
  19. Keeney, Ralph L., and Howard Raiffa, "Decisions with multiple objectives: preferences and value tradeoffs," Cambridge university press, 1993.