Long range dependent job arrival process and its implications in grid environments, in
Hui Li · 2007
Job arrivals can be described as point processes and it is shown that correlations and fractal behavior can be reli-ably revealed using the count/rate representation. Using real workload data from production Grids, we show that the second order properties such as the autocorrelation func-tion (ACF) and the scaling behavior can be well recon-structed by a Multifractal Wavelet Model (MWM). A so-called controlled-variability integrate-and-fire (CV-InF) al-gorithm is applied to transform rates into interarrivals so that a full description of the arrival process can be obtained. The additive nature of rates makes it possible to model dif-ferent patterns separately and aggregate them back to form a unified process. We further quantify the performance im-pacts of autocorrelated job arrivals in Grid scheduling using model-driven simulation. It is shown that autocorrelations in the arrival processes can cause performance degradation both at the local and the Grid level.