A scheduling approach with respect to overlap of computing and data transferring in grid computing

In this paper, we present a two-level distributed schedule model, and propose a scheduling approach with respect to overlap of computing and data transferring. On the basis of network status, node load, and the relation between task execution and task data access, data transferring and computing can occur concurrently in the following three cases: a) A task is being executed on a part of its dataset when the other of its dataset is being replicated; b) A dataset of a scheduled task is being replicated to a node, at which another task is running; c) Data exchange happens when dependant subtasks are running at different nodes. Corresponding theoretical analysis and experimental results demonstrate that the scheduling approach improves execution performance and resource utilization.