  Conventional wisdom for minimizing the average flow completion time (AFCT) in
the datacenter network (DCN), where flow sizes are highly variable, would
suggest scheduling every individual flow. However, we show that considering
scheduling delay (including scheduler's computational and communication
delays), serving most of the flows without any scheduling and only in
first-come-first-served (FCFS) manner significantly improves their performance
even when it is compared to the shortest remaining processing time (SRPT)-known
as optimum algorithm when scheduling delay is zero. To do so, we only require
to have two coarse classes of flows categorized based on flows' sizes
(1st-class including flows smaller than a threshold, H, and 2nd-class including
others) and serve 1st-class flows always before serving 2nd-class ones. To show
that, we take SRPT scheduling algorithm accompanied by the global knowledge of
flows, formulate impact of scheduling delay on its performance, and prove that
for any flow size distribution and network load (<1), there is always a
threshold, H, which guarantees 1st-class flows achieve lower AFCT under FCFS
compared to SRPT. Our numerically calculated results and extensive flow-level
simulations show that on average, more than 90% of flows could be in 1st-class
and consequently do not require any scheduling.
