Abstract
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.
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Zhao, H., Sakellariou, R. (2004). A Low-Cost Rescheduling Policy for Dependent Tasks on Grid Computing Systems. In: Dikaiakos, M.D. (eds) Grid Computing. AxGrids 2004. Lecture Notes in Computer Science, vol 3165. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28642-4_3
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DOI: https://doi.org/10.1007/978-3-540-28642-4_3
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