Journal of the Korea Convergence Society (한국융합학회논문지)

Korea Convergence Society (한국융합학회)
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An Predictive Analytics based on Goal-Scenario for Self-adaptive System

자가적응형 시스템을 위한 목표 시나리오 기반 예측 분석

  • Baek, Su-Jin (Department of Information Communication, Yong-In Songdam College)
  • 백수진 (용인송담대학교 정보통신학과)
  • Received : 2017.10.02
  • Accepted : 2017.11.20
  • Published : 2017.11.28
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Abstract

For efficient predictive analysis, self-healing research is needed that enables the system to recover autonomously by self-cognition and diagnosing system problems. However, software development does not provide formal contextual information analysis and appropriate presentation structure according to external situation. In this paper, we propose a prediction analysis method based on the change contents by applying the extraction rule to the functions that can act, data, and transaction based on the new Goal-scenario. We also evaluated how well the predictive analysis met through the performance indicators for achieving the requirements goal. Compared with the existing methods, the proposed method has a maximum 32.8% higher matching result through performance measurement, resulting in a 28.9% error rate and a 45.8% reduction in the change code. This shows that it can be processed into a serviceable form through rules, and it shows that performance can be expanded through predictive analysis of changes.

효율적인 예측 분석을 위해서는 문제를 스스로 인식하고 진단하여 시스템이 자율적으로 복구가 가능한 자가 치유 연구가 필요하다. 그러나, 소프트웨어를 개발하는데 있어서 외부상황에 따른 정형화된 컨텍스트 정보 분석 및 적절한 표현 구조를 제시하지 못한다. 본 논문에서는 새로운 목표 시나리오를 기반으로 행위 요소, 데이터, 트랜잭션이 가능한 기능들에 대해 추출 규칙을 적용하여 변경 내용에 따른 예측 분석 방법을 제안한다. 그리고, 요구사항 목표 달성을 위한 성과지표를 통해 예측 분석 내용이 얼마나 부합되었는지 평가하였다. 제안한 방법이 기존 방법들에 비해 성과측정을 통한 부합 결과는 최고 32.8% 높았고, 이에 따른 오차율은 28.9%, 변경 코드는 최고 45.8%가 감소되었다. 이는 목표 시나리오 기반 컨텍스트 규칙을 통해 서비스 가능한 형태로 가공할 수 있음을 보여주며, 문제 발생에 대한 변경 내용을 예측 분석을 통한 성능의 확장이 가능함을 보여준다.

Keywords

References

  1. G. Shmueli and O. Koppius, "Predictive analytics in information systems research," Robert H. Smith School Research Paper No. RHS, pp. 06-138, 2010.
  2. Anwaar Ali, JunaidQadir, RaihanurRasool, ArjunaSathiaseelan, Andrej Zwitter and Jon Crowcroft "Big data for development: applications and techniques" Ali et al. Big Data Analytics, DOI 10.1186/s41044-016-0002-4. 2016.
  3. Shmueli, G., & Koppius, O. "Predictive analytics in information systems research", MIS Quarterly, 35(3), 553-572, 2011 https://doi.org/10.2307/23042796
  4. R. D. Lemos et al., "Software engineering for selfadaptive systems: A second research roadmap," Software Engineering for Self-Adaptive Systems II, pp. 1-32, 2013.
  5. J. H. Kim, D. Lee., K. Y. Chung,, Item recommendation based on context-aware model for personalized u-healthcare service Multimedia Tools and Applications. doi:10.1007/s11042-011-0920-0., 2013
  6. S. J. Baek., S. H. Sim, Y. J. Song, "An Automated Code Generation for Dynamic reconfiguration based on Goal-Scenario", The Journal of Digital Policy & Management, Vol 10, No. 1, pp. 349-355, 2. 2012.
  7. S. J. Hwang. J. S. Park, M.Y. Moon, K. H. Yeom, "An Approach for Designing Self-Adaptive Software based on Context Information", The Korean Institute of Information Scientists and Engineers Autumn Conference, vol 33, No. 2(c), pp. 354-359, 2006.
  8. David S. Wile and Alexander Egyed, "An Externalized Infrastructure for Self-Healing Systems", proceedings of the 4th Working IEEE/IFIP Conference on Software Architecture, pp. 285-288, Sep. 2004.
  9. Michael E. Shin, and Jung Hoon An, "Self-Reconfiguration in Self-Healing System", Proceedings of the 3th IEEE International Workshop on Engineering of Autonomic & Autonomic System, pp. 89-98, Mar., 2006.
  10. J. J. Choi, J. H. Jeon, "Real-Time Predictive Security Framework Design For U-Health Service", Proceeding of Korea Information and Communications Society (KICS) Autumn Conference, pp. 26-27, 2016.
  11. Stefanie Rinderle, Manfred Reichert, Peter Dadam, "Correctness criteria for dynamic changes in workflow systems-a survey", Data & Knowledge Engineering 50, pp. 9-34, 2004 https://doi.org/10.1016/j.datak.2004.01.002
  12. Aalst, W. M. P. V. D., Weske, M., Wirtz, G. "Advanced topics in workflow management: Issues, requirements, and solutions". International Journal of Integrated Design and Process Science, 7(3). 2003.
  13. Weber, B., Reichert, M., & Rinderle-Ma, S. "Change Pattern and changes support features enhancing flexibility in process-aware information systems". Data and Knowledge Engineering, 66(3), 438-466. 2008. https://doi.org/10.1016/j.datak.2008.05.001
  14. S. J. Baek, An Analysis of Context Basis for Dynamic Reconfiguration of Self-Adaptive Software, KyungHee University, Ph.D. thesis, 2012.
  15. J. W. Park, J. H. Choi, P. Y. Cho, N. Y. Lee, "Process Performance Measurement Model Based on Event for an efficient Decision-Making", The KIPS Transactions : Part D, Vol. 17, No. 4, 8, 2010.