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Fuzzy approach to complex system analysis

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents a new approach to reliability and functional analysis of sophisticated complex systems using fuzzy logic. We propose to use such methodology since dependability parameters of the system are mostly approximated by experts instead of classical sources of data. Presented approach show different idea – modeling system using the unified structure – in functional sense. We assess the reliability of the system by accumulated down time. Fuzzy logic based reliability analysis, as well as Computer Information System and Discrete Transport System modeling and simulation are presented. Moreover, results of numerical experiment performed on a test case scenario related to the economic and functional aspects using proposed methodology are given. Fuzzy approach allows reducing the problem of assumptions of reliability distributions and – this way – seems to be very interesting for real systems management and tuning.
Słowa kluczowe
Rocznik
Strony
169--178
Opis fizyczny
Bibliogr. 22 poz., rys., wykr.
Twórcy
  • Wrocław University of Technology, Poland
autor
  • Wrocław University of Technology, Poland
autor
  • Wrocław University of Technology, Poland
Bibliografia
  • [1] Barlow, R. & Proschan, F. (1996). Mathematical Theory of Reliability. Philadelphia: Society for Industrial and Applied Mathematics.
  • [2] Chan, K.S., Bishop, J., Steyn, J., Baresi, L. & Guinea, S. (2009). A Fault Taxonomy for Web Service Composition. In: Di Nitto, E., Ripeanu, M. (eds.) ICSOC 2007. LNCS Springer, Heidelberg, vol. 4907, 363-375.
  • [3] Conallen, J. (2000). Building Web Applications with UML. Addison Wesley Longman Publishing Co., Amsterdam.
  • [4] Davila-Nicanor, L. & Mejia-Alvarez, P. (2004). Reliability Improvement of Web-Based Software Applications. Proceedings of Quality Software, QSIC 2004, September 8-9, 180-188.
  • [5] Fishman, G. (1996). Monte Carlo: Concepts, Algorithms, and Applications. Springer-Verlag.
  • [6] Hongli Y., Xiangpeng Z., Zongyan Q., Geguang P., & Shuling W. (2006). A Formal Model for Web Service Choreography Description Language (WS-CDL), Proc. of ICWS 2006, IEEE Computer Society.
  • [7] Jennings, N. R. (2000). On Agent-Based Software Engineering. Artificial Intelligence 117, Elsevier Press, 277-296.
  • [8] Ma, L. & Tian, J. (2007). Web Error Classification and Analysis for Reliability Improvement. Journal of Systems and Software 80 (6), 795-804.
  • [9] Martinello, M., Kaaniche, M. & Kanoun, K. (2005). Web Service Availability-Impact of Error Recovery and Traffic Model. Safety, Reliability Engineering & System Safety 89 (1), 6-16.
  • [10] Mascal, C. M. & North, M.J. (2005). Tutorial on Agent-Based Modelling and Simulation. Winter Simulation Conference.
  • [11] Mazurkiewicz, J. & Walkowiak, T. (2003). Fuzzy Reliability Analysis. ICNNSC 2002 - 6th International Conference Neural Networks and Soft Computing. Advances in Soft Computing, 298-303. Physica-Verlag, Heidelberg.
  • [12] Mazurkiewicz, J., & Walkowiak, T. (2004). Fuzzy Economic Analysis of Simulated Discrete Transport System. Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds.) ICAISC 2004. LNCS (LNAI) Springer, Heidelberg, vol. 3070, 1161-1167.
  • [13] Mellouli, S., Moulin B., & Mineau, G. W. (2003). Laying Down the Foundations of an Agent Modelling Methodology for Fault-Tolerant Multi-agent Systems, ESAW, 275-293.
  • [14] Michalska, K., Mazurkiewicz, J. (2011). Functional and Dependability Approach to Transport Services Using Modelling Language. Springer LNCS/LNAI, LNAI 6923, SpringerVerlag Berlin Heidelberg, P. Jędrzejowicz et al. (Eds.), 180-190
  • [15] Nicol, D., Liu J., Liljenstam, M. & Guanhua, Y. (2003). Simulation of Large Scale Networks Using SSF. Proceedings of the 2003 Winter Simulation Conference, Vol. 1. 650-657.
  • [16] Nowak, K. & Mazurkiewicz, J. (2011). Multiagent Modeling and XML-Like Description of Discrete Transport System. Transport and Telecommunication, Editor: I. Kabashkin, Transport and Telecommunication Institute, Riga, Latvia, Vol. 12, No. 4, 14-26.
  • [17] Silverman, B.W. (1986). Density Estimation. Chapman and Hall, London.
  • [18] Walkowiak, T. & Mazurkiewicz, J. (2009). Analysis of Critical Situations in Discrete Transport Systems. Proceedings of International Conference on Dependability of Computer Systems, Brunow, Poland, June 30-July 2, 2009. Los Alamitos: IEEE Computer Society Press. 364-371.
  • [19] Walkowiak, T., & Mazurkiewicz, J. (2008). Availability of Discrete Transport System Simulated by SSF Tool. Proceedings of International Conference on Dependability of Computer Systems, Szklarska Poreba, Poland, June, 2008. Los Alamitos: IEEE Computer Society Press, 430-437.
  • [20] Walkowiak, T. & Mazurkiewicz, J. (2008). Functional Availability Analysis of Discrete Transport System Realized by SSF Simulator. Computational Science - ICCS 2008, 8th International Conference, Krakow, Poland, June 2008. Springer-Verlag, LNCS 5101, Part I. 671-678
  • [21] Walkowiak, T., & Mazurkiewicz, J. (2010). Algorithmic Approach to Vehicle Dispatching in Discrete Transport Systems. Technical approach to dependability / Ed. by Jarosław Sugier, et al. Wroclaw: Oficyna Wydawnicza Politechniki Wroclawskiej. 173-188.
  • [22] Walkowiak, T., & Mazurkiewicz, J. (2010). Functional Availability Analysis of Discrete Transport System Simulated by SSF Tool. International Journal of Critical Computer Based Systems, Vol. 1, No 1-3. 255-266.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8aebd01c-a3a8-46a8-a0e4-5e846398a920
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