Model-based simulation and performance evaluation of grid scheduling strategies

Simulation studies of Grid scheduling strategies require representative workloads to produce dependable results. Real production Grid workloads have shown diverse correlation structures and scaling behavior, which are different to the characteristics of the available supercomputer workloads and cannot be captured by Poisson or simple distribution-based models. We present statistical models that are able to reproduce various autocorrelation structures, including pseudo-periodicity and long range dependence. By conducting model-based simulation, we quantitatively evaluate the performance impacts of workload autocorrelations in Grid scheduling. The results indicate that autocorrelations result in system performance degradation, both at the local and the Grid level. It is shown that realistic workload modeling is not only possible, but also necessary to enable dependable Grid scheduling studies.