Stochastic Approach to Scheduling Multiple Divisible Tasks on a Heterogeneous Distributed Computing System

Heterogeneity has been considered in scheduling, but without taking into account the temporal variation of completion times of the sub-tasks for a divisible, independent task. In this paper, the problem of scheduling multiple, divisible independent tasks on a heterogeneous distributed computing system are addressed. The "stochastic" approach, which was previously applied to DAG scheduling, is employed for scheduling a group of multiple divisible as well as whole independent tasks. It explicitly considers the standard deviations (temporal heterogeneity) in addition to the mean execution times in deriving a schedule, in order to model more closely what would actually happen "on average" on a temporally heterogeneous system (instead of approximating the random weights by their means only as in other approaches). Through an extensive computer simulation, it has been shown that the proposed approach can improve schedules significantly over those by a scheme which uses the average weights only.