Automatic temporal and spatial modeling of read request
读请求的空间与时间特征建模

In order to improve I/O performance of parallel applications and parallel file systems,an automatic modeler was presented to model and predict for read request temporal and spatial series.It used autocorrelation function and Haar wavelet transform technology to automatically identify and build Autoregressive Integrated Moving Average(ARIMA) models of interarrival times.It used Markov modeler to model and forecast spatial series.Our prefetching method can combine ARIMA time series predictions and Markov model spatial predictions to adaptively determine when,what,and how many data blocks to be prefetched.