1 research outputs found
Stochastic Non-preemptive Co-flow Scheduling with Time-Indexed Relaxation
Co-flows model a modern scheduling setting that is commonly found in a
variety of applications in distributed and cloud computing. A stochastic
co-flow task contains a set of parallel flows with randomly distributed sizes.
Further, many applications require non-preemptive scheduling of co-flow tasks.
This paper gives an approximation algorithm for stochastic non-preemptive
co-flow scheduling. The proposed approach uses a time-indexed linear
relaxation, and uses its solution to come up with a feasible schedule. This
algorithm is shown to achieve a competitive ratio of
for zero-release
times, and for general
release times, where represents the upper bound of squared coefficient
of variation of processing times, and is the number of servers.Comment: Some of the results have been fixed, mainly involving the CoV. The
changes compared to the previous version are mino