by applying the conception of genetic algorithm into the parameters turning process of I/O schedule strategy
it takes strategy parameters adapting the storage system according to the periodical statistic of I/O operation
and got a group of strategy parameters
which have the best adaption in real-time storage environment
and makes the I/O schedule strategy have a better performance. In the new way of tuning strategy parameters
it makes the strategy parameters resuming its convergence in a short time. The experimental results show that
in the storage system which is running long term and have a heavy load
the efficiency of computers I/O operation which applies this papers strategy has an obvious performance promotion than applying others.
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references
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