EURO Working Group on Stochastic Modelling

FIRST MEETING: 19-21 APRIL 2006, AMSTERDAM

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Abstracts

Menno Dobber, An Effective Prediction Method for Running Times of Jobs on Shared Processors

Grid computing is an emerging technology by which huge numbers of processors over the world create a global source of processing power. Their collaboration makes it possible to perform computations that are too extensive to perform on a single processor. On a grid processors may connect and disconnect at any time, and the load on the computers can be highly bursty. Those characteristics raise the need for the development of techniques that make grid applications robust against the dynamics of the grid environment. In particular, applications that use significant amounts of processor power for running jobs need effective predictions of the expected computation times of those jobs on remote hosts. Currently, there are no effective prediction methods available that cope with the ever-changing running times of jobs on a grid environment. Motivated by this, we develop the Dynamic Exponential Smoothing (DES) method to predict running times in a grid environment. We have performed extensive experiments in a real global-scale grid enviroment to compare the effectiveness of DES. The results demonstrate that DES strongly and consistently outperforms existing prediction methods.