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.
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Tian, D., Chen, S., Mao, T. (2007). Fuzzy-Grey Prediction Based Dynamic Failure Detector for Distributed Systems. In: Jin, H., Rana, O.F., Pan, Y., Prasanna, V.K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2007. Lecture Notes in Computer Science, vol 4494. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72905-1_12
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DOI: https://doi.org/10.1007/978-3-540-72905-1_12
Publisher Name: Springer, Berlin, Heidelberg
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