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As a validation of the introduced functionality, we simulate the impact of instability on scientific workflow scheduling by assessing and comparing the performance of four schedulers in the course of several experiments both in simulation and on real cloud infrastructure.
Data-intensive: Data-aware workflow scheduling.
Our algorithm showed noticeable enhancements over the classical workflow scheduling algorithms.
In this paper, we address the problem of resource-efficient workflow scheduling.
In [30], various strategies for provisioning of virtual machines and workflow scheduling are described.
The focus of [12, 13] is on describing workflow scheduling algorithms for grids.
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To this end, we present the Maximum Effective Reduction (MER) algorithm, a resource efficiency solution that optimizes the resource usage of a workflow schedule generated by any particular scheduling algorithm.
MER trades the minimal makespan increase for the maximal resource usage reduction by consolidating tasks with the exploitation of resource inefficiency in the original workflow schedule.
The focus of this paper is on workflows scheduling in cloud computing, which is gaining a lot of attention recently because workflows have emerged as a paradigm to represent complex computing problems.
This is important for the sole reason that Grape is a communication solution, primarily, with our language processing functioning as a kind of smart assistant in the background, to automate workflows, schedule meetings and assign tasks".
In such workflows, when scheduling tasks to distributed resources, the data transfers between tasks are not a negligible factor and may comprise a significant portion of the total execution time and cost.
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job scheduling
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process scheduling
stream scheduling
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flow control scheduling
working scheduling
workflow tool
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workflow orchestration
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workflow research
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