Assessing the Impact of Supporting Information on the Scheduling of Scientific Workflows on Clouds

  • Eduardo Cotrin Teixeira
  • Daniel Cordeiro
  • Kelly Rosa Braghetto

Resumo


Executing scientific workflows in high-performance cloud computing platforms requires the use of scheduling algorithms that allow workflows execution as fast as possible, while minimizing the monetary cost of such executions. In this work we study how the use of supporting information can offer guidance to scheduling algorithms, helping them to devise more efficient execution plans in terms of the total execution time (makespan) and the total monetary cost. Using two large-scale scientific workflows, our experiments showed that simple modifications on a classical scheduling algorithm (HEFT), in conjunction with the appropriate supporting information, could reduce the monetary cost of an execution in up to 59% and reduce the makespan in up to 8.6%.

Publicado
06/07/2018
TEIXEIRA, Eduardo Cotrin; CORDEIRO, Daniel; BRAGHETTO, Kelly Rosa. Assessing the Impact of Supporting Information on the Scheduling of Scientific Workflows on Clouds. In: BRAZILIAN E-SCIENCE WORKSHOP (BRESCI), 12. , 2018, Natal. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2018 . ISSN 2763-8774. DOI: https://doi.org/10.5753/bresci.2018.3277.