The paper lists three major issues: complexity, time and uncertainty, and identifies dependability as the permanent challenge. In order to enhance dependability, the paradigm shift is proposed where focus is on failure prediction and early malware detection. Failure prediction methodology, including modeling and failure mitigation, is presented and two case studies (failure prediction for computer servers and early malware detection) are described in detail. The proposed approach, using predictive analytics, may increase system availability by an order of magnitude or so.
CITATION STYLE
Malek, M. (2017). Predictive analytics: A shortcut to dependable computing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10479 LNCS, pp. 3–17). Springer Verlag. https://doi.org/10.1007/978-3-319-65948-0_1
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