A Low-Cost Rescheduling Policy for Dependent Tasks on Grid Computing Systems

A simple model that can be used for the representation of certain workflows is a directed acyclic graph. Although many heuristics have been proposed to schedule such graphs on heterogeneous environments, most of them assume accurate prediction of computation and communication costs; this limits their direct applicability to a dynamically changing environment, such as the Grid. To deal with this, run-time rescheduling may be needed to improve application performance. This paper presents a low-cost rescheduling policy, which considers rescheduling at a few, carefully selected points in the execution. Yet, this policy achieves performance results, which are comparable with those achieved by a policy that dynamically attempts to reschedule before the execution of every task.