One of the main challenges in volunteer computing systems is scheduling large-scale applications expressed as scientific workflows. This work aims to integrate partitioning scientific workflows and proximity-aware resource provisioning to increase the percentage of workflows that meet the deadline in peer-to-peer based volunteer computing systems. In the partitioning phase, a scientific workflow is partitioned into sub-workflows in order to minimize data dependencies among them. We utilize knowledge-free load balancing policy and proximity of resources to distribute sub-workflows on volunteer resources. Simulation results show that the proposed workflow scheduling system improves the percentage of scientific workflows that meet the deadline with average of 18% under a moderate workload. © Springer International Publishing Switzerland 2013.
CITATION STYLE
Ghafarian, T., & Javadi, B. (2013). Deadline-constrained workflow scheduling in volunteer computing systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8285 LNCS, pp. 44–57). https://doi.org/10.1007/978-3-319-03859-9_4
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