  Despite the fact that size-based schedulers can give excellent results in
terms of both average response times and fairness, data-intensive computing
execution engines generally do not employ size-based schedulers, mainly because
of the fact that job size is not known a priori.
  In this work, we perform a simulation-based analysis of the performance of
size-based schedulers when they are employed with the workload of typical
data-intensive schedules and with approximated size estimations. We show
results that are very promising: even when size estimation is very imprecise,
response times of size-based schedulers can be definitely smaller than those of
simple scheduling techniques such as processor sharing or FIFO.
