Abstract
Development of dependable applications requires selection of appropriate fault tolerance techniques that balance efficiency in fault handling and resulting consequences, such as increased development cost or performance degradation. This paper describes an advisory system that recommends fault tolerance techniques considering specified development and runtime application attributes. In the selection process, we use the K-means clustering algorithm to identify similarities between known fault tolerance techniques to select those ones that are possibly different, but simultaneously conform to developer specification. As a part of the research, we implemented a web-based system that covers definition of attributes, aggregates knowledge about fault tolerance techniques together, and implements the advisory algorithm.
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References
Chitnis, L., Dobraa, A., Ranka, S.: Fault tolerant aggregation in heterogeneous sensor networks. Journal of Parallel and Distributed Computing (2009)
European Network of Excellence ReSIST, Resilience for Survivability in IST, http://www.resist-noe.org
Garcia, A., Rubira, C., Romanovsky, A., Xu, J.: A comparative study of exception handling mechanisms for building dependable object-oriented software. Journal of Systems and Software (2001)
Gashi, I., Popov, P., Strigini, L.: Fault tolerance via diversity for off-the-shelf products: A study with sql database servers. IEEE Transactions on Dependable and Secure Computing (October- December 2007)
Helmer, O., Rescher, N.: On the epistemology of the inexact science. Management Science 6(1) (1959)
Jalote, P.: Fault Tolerance in Distributed Systems. Prentice Hall PTR (1998)
Jang, L., Eberlein, A., Far, B., Mousavi, M.: A methodology for the selection of requirements engineering tehniques. Software and Systems Modeling 7 (2007)
Kaczmarek, P.L.: Ontology Supported Selection of Versions for N-Version Programming in Semantic Web Services. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2008, Part I. LNCS, vol. 5101, pp. 317–326. Springer, Heidelberg (2008)
Koren, I., Krishna, C.: Fault-Tolerant Systems. Elsevier B.V. (2007)
Krawczyk, H., Wiszniewski, B.: Analysis and Testing of Distributed Software Applications. Research Studies Press (1998)
Laprie, J.C., Randell, B., Aviienis, A.: Fundamental concepts of dependability. Tech. rep., LAAS-CNRS (2000)
Manning, C.D., Raghavan, P., Schtze, H.: An Introduction to Information Retrieval. Cambridge University Press, Cambridge (2009)
Pullum, L.: Software Fault Tolerance Techniques and Implementation. Artech House (2001)
Townend, P., Xu, J.: Replication-based fault tolerance in a grid environment. In: U.K. e-Science 3rd All-Hands Meeting (2004)
Xie, Z., Sun, H., Saluja, K.: A survey of software fault tolerance techniques (2008)
Yuan, L., Dong, J.S., Sun, J., Basit, H.A.: Generic fault tolerant software architecture reasoning and customization. IEEE Transactions on Reliability (September 2006)
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Kaczmarek, P.L., Roman, M.Ł. (2012). A Clustering-Based Methodology for Selection of Fault Tolerance Techniques. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7268. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29350-4_77
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DOI: https://doi.org/10.1007/978-3-642-29350-4_77
Publisher Name: Springer, Berlin, Heidelberg
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