Abstract
Scheduling tasks with precedence constraints on a set of resources with diffe rent performances is a well-known NP-co mplete proble m, and a nu mber of e ffective heuristics has been proposed to solve it. If the start time and the deadline for each specific workflow are known (for e xa mple, if a workflow starts execution according to periodic data coming fro m the sensors, and its execution should be completed before data acquisition), the proble m of mu ltip le deadline -constrained workflows scheduling arises. Taking into account that resource providers can give only restricted access to their computational capabilities, we consider the case when resources are partia lly available for workflow e xecution. To address the problem described above, we study the scheduling of deadline -constrained scientific wo rkflo ws in non-dedicated heterogeneous environment. In this paper, we introduce three scheduling algorith ms for mapping the tasks of mu ltiple workflows with different deadlines on the static set of resources with previously known free t ime windows. Simu lation e xperiments show that scheduling strategies based on a proposed staged scheme give better results than merge -based approach considering all workflows at once.
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