Abstract
Fuzzy logic and grey theory, combined with adaptive heartbeat mechanism, are integrated to implement an adaptive failure detector for distributed systems. A GM(1,1) unified-dimensional new message model, which only needs a small volume of sample data, is used to predict heartbeat arrival time dynamically. Since prediction error is inevitable, a two-input (residual ratio and message loss rate), one-output (compensation value) fuzzy controller is designed to learn how to compensate for the output from the grey model, and the roughly determined fuzzy rule base is tuned by a reward-punishment learning principle. Experimental results show the availability and validity of the failure detector in detail. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Tian, D., Chen, S., & Mao, T. (2007). Fuzzy-grey prediction based dynamic failure detector for distributed systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4494 LNCS, pp. 131–141). Springer Verlag. https://doi.org/10.1007/978-3-540-72905-1_12
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