COTS 하드웨어 컴포넌트 기반 임베디드 소프트웨어 신뢰성 모델링

Embedded Software Reliability Modeling with COTS Hardware Components

  • 구태완 (한국과학기술원 정보통신공학과) ;
  • 백종문 (한국과학기술원 전산학과)
  • 발행 : 2009.08.15

초록

최근 IT 산업은 국방, 항공, 자동차, 의료와 같은 전통 산업분야와 서로 융합하는 추세이다. 그러므로 시스템의 하드웨어를 주로 담당하는 임베디드 소프트웨어는 높은 신뢰성, 가용성, 유지보수성이 보장되어야 한다. 이를 위해 최근 COTS (Commercial Off The Shelf) 하드웨어 컴포넌트 기반 임베디드 소프트웨어를 개발하는 추세이다. 그러나 이러한 개발방법에는 일반적 소프트웨어 결함 외에 하드웨어와의 상호작용에 기인하는 결함이 추가적으로 발생할 수 있다. 이를 연동결함(Linkage Fault)라고 정의한다. 이는 발생 빈도가 낮음에도 불구하고 전체 시스템의 중단을 야기할 정도로 위험하다. 본 논문에서는 COTS 하드웨어 컴포넌트 기반 임베디드 소프트웨어 개발 시 이러한 연동결함의 발생을 고려한 신뢰성 모델을 제안한다. 또한 제안된 모델의 타당성을 분석하기 위해 베이지안 분석과 마코프 체인 몬테카를로 방법으로 계산한 베이즈 요인을 이용한다. 끝으로 IT 융합 분야의 실제 데이터를 활용하여 제안된 모델의 이론적 결과를 뒷받침한다.

There has recently been a trend that IT industry is united with traditional industries such as military, aviation, automobile, and medical industry. Therefore, embedded software which controls hardware of the system should guarantee the high reliability, availability, and maintainability. To guarantee these properties, there are many attempts to develop the embedded software based on COTS (Commercial Off The Shelf) hardware components. However, it can cause additional faults due to software/hardware interactions beside general software faults in this methodology. We called the faults, Linkage Fault. These faults have high severity that makes overall system shutdown although their occurrence frequency is extremely low. In this paper, we propose a new software reliability model which considers those linkage faults in embedded software development with COTS hardware components. We use the Bayesian Analysis and Markov Chain Monte-Cairo method to validate the model. In addition, we analyze real linkage fault data to support the results of the theoretical model.

키워드

참고문헌

  1. Alfredo Benso and Paolo Prinetto, 'Fault Injection Techniques and Tools for Embedded Systems Reliability Evaluation,' Sringer, 2003
  2. Vijaykrishnan Narayanan and Yuan Xie, 'Reliability Concerns in Embedded Systems Designs,' IEEE Computer, vol.39, no.1, pp.118-120, 2006 https://doi.org/10.1109/MC.2006.31
  3. Steve Manuel and Dan Lincoln, 'COTS-Based SoC Technology Benefits Defense and Aerospace Electronics Applications,' http://www.ecnmag.com, June, 2005
  4. LinuxElectron, 'Embedded Military COTS Market to Reach $3.25 Billion By 2008,' http://www.linuxelectrons. com/news/embedded/embedded-military-c ots-market-reach-3-25-billion-2008, 2004
  5. VDC Research Group, 'Embedded COTS systems in Military, Aerospace, and Defense Applications - Third Edition A Market Demand Analysis Volume I: North American & Volume II: European,' 2006
  6. Ravishankar K. Iyer and Paola Velardi, 'Hardware- Related Software Errors: Measurement and Analysis,' IEEE Transactions on Software Engineering, vol.SE-11, no.2, pp.223-232, Feb. 1985 https://doi.org/10.1109/TSE.1985.232198
  7. Kapsu Kim and Chisu Wu, 'A Software Reliability Model in the Embedded System,' Proc. of the First International Conference on Software Testing, Reliability and Quality Assurance, 1994
  8. Norman F. Schneidewind, 'Reliability Modeling for Safety-Critical Software,' IEEE Transactions on Reliability, vol.46, no.1, pp.88-98, 1997 https://doi.org/10.1109/24.589933
  9. Naruemon Wattanapongsakorn, 'Integrating Dependability Analysis and Optimization into the Distributed Embedded System Design Process,' Ph.D., School of Electrical Engineering, University of Pittsburgh, 2000
  10. Naruemon Wattanapongsakorn and Steven P. Levitan, 'Reliability Optimization Models for Embedded Systems With Multiple Applications,' IEEE Transactions on Reliability, vol.53, no.3, pp.406-417, Sep. 2004
  11. Xiaolin Teng and Hoang Pham and Daniel R. Jeske, 'Reliability Modeling of Hardware and Software Interactions, and Its Applications,' IEEE Transactions on Reliability, vol.55, no.4, pp.571-578, Dec. 2006 https://doi.org/10.1109/TR.2006.884589
  12. Javier Cano and David Rios, 'Reliability Forecasting in Complex ardware/Software Systems,' Proc. of the First International Conference on Availability, Reliability and Security (ARES'06), 2006 https://doi.org/10.1109/ARES.2006.106
  13. Shankar, V. and Milton, J. C. and Mannering, F. L., 'Modeling accident frequencies as zeroaltered probability process: An empiral inquiry,' Accident Analysis and Prevention, vol.29, no.6, 1997 https://doi.org/10.1016/S0001-4575(97)00052-3
  14. Newton, M. A. and A. E. Raftery, 'Approximate Bayesian Inference by the Weight Likelihood Bootstrap (with Discussion),' Journal of the Royal Statistical Society, Series B, vol.56, pp.3-48, 1994
  15. Jang H. J. and Kang Y. H. and Lee S. and Kim S. W., 'Bayesian Analysis for the Zero-Inflated Regression Models,' The Korean Journal of Applied Statistics, vol.21, no.4, pp.603-613, 2008 https://doi.org/10.5351/KJAS.2008.21.4.603
  16. Jansakul, N. and Hinde, J. P., 'Score Tests for Zero-Inflated Poisson Models,' Computational Statistics and Data Analysis, vol.40, pp.75-96, 2002 https://doi.org/10.1016/S0167-9473(01)00104-9
  17. Hoang Pham, 'System Software Reliability,' Springer, 2006
  18. Irene Eusgeld and Bernhard Fechner and Felix Salfner and Max Walter and Philipp Limbourg and Lijun Zhang, 'Hardware Reliability,' Lecture Notes in Computer Science, Springer, 2008
  19. Neil Steiner and Peter Athanas, 'Hardware- Software Interaction: Preliminary Observations,' Proc. of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05), 2005
  20. Lee Bain and Max Englehardt, 'Statistical Analysis of Reliability and Life-Testing Models: Theory and Methods, 2nd Edition,' Chemical Rubber Company (CRC) Press, 1991
  21. B. Craig Meyers and Patricia Oberndorf, 'Managing Software Acquisition: Open Systems and COTS Products,' SEI, 1996
  22. Peter Congdon, 'Bayesian Statistical Modeling,' John Wiley and Sons, Ltd., 2006
  23. S. Geman and Donald Geman, 'Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images,' IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.6, pp.721-741, 1984 https://doi.org/10.1109/TPAMI.1984.4767596
  24. The Comprehensive R Archive Network, http:// cran.r-project.org/