An Experimental Study of Data Transfer Strategies for Execution of Scientific Workflows

  • Oleg SukhoroslovEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11657)


The paper studies the impact of data transfer strategies on the execution of scientific workflows. Five strategies are described, which define when and in what order data transfers are performed during the workflow execution. The strategies are experimentally evaluated by means of simulation using a realistic network model. It is demonstrated that the execution time of data-intensive workflows significantly depends on the used strategy. In particular, Eager and Lazy strategies, often used in theory and practice of workflow scheduling, demonstrate the poor results in most cases. The alternative strategies provide up to 36% makespan improvement by overlapping communications and computations, prioritizing data transfers and reducing network contention.


Scientific workflows Data-intensive computing Task scheduling Data management Simulation 



This work is supported by the Russian Science Foundation (project 16-11-10352).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute for Information Transmission Problems of the Russian Academy of SciencesMoscowRussia

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