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English Information

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Authors
# Name
1 Wesley Ferreira(wesleyferreira@id.uff.br)
2 Liliane Kunstmann(lneves@cos.ufrj.br)
3 Aline Paes(alinepaes@ic.uff.br)
4 Marcos Bedo(marcosbedo@id.uff.br)
5 Daniel de Oliveira(danielcmo@ic.uff.br)

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Reference
# Reference
1 Babuji, Y. N. et al. (2019). Parsl: Pervasive parallel programming in python. In Weissman, J. B., Butt, A. R., and Smirni, E., editors, HPDC’19, pages 25–36. ACM.
2 Burkat, K., Pawlik, M., Balis, B., Malawski, M., Vahi, K., Rynge, M., da Silva, R. F., and Deelman, E. (2021). Serverless containers – rising viable approach to scientific workflows. In eScience, pages 40–49
3 Carrion, C. (2023). Kubernetes scheduling: Taxonomy, ongoing issues and challenges. ACM Comput. Surv., 55(7):138:1–138:37
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15 Ogasawara, E. S., Dias, J., Silva, V., Chirigati, F. S., de Oliveira, D., Porto, F., Valduriez, P., and Mattoso, M. (2013). Chiron: a parallel engine for algebraic scientific workflows. Concurr. Comput. Pract. Exp., 25(16):2327–2341
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17 Shah, S. T., Lahaye, R. J. W. E., Kazmi, S. A. A., Chung, M. Y., and Hasan, S. F. (2014). Htcondor system for running extensive simulations related to D2D communication. In ICTC, pages 283–284. IEEE
18 Silva, V., de Oliveira, D., Valduriez, P., and Mattoso, M. (2018). Dfanalyzer: runtime dataflow analysis of scientific applications using provenance. Proceedings of the VLDB Endowment, 11(12):2082–2085
19 Struhár, V., Behnam, M., Ashjaei, M., and Papadopoulos, A. V. (2020). Real-time containers: A survey. In Fog-IoT, volume 80 of OASIcs, pages 7:1–7:9
20 Teylo, L., de Paula Junior, U., et al. (2017). A hybrid evolutionary algorithm for task scheduling and data assignment of data-intensive scientific workflows on clouds. FGCS, 76:1–17
21 Zheng, C., Tovar, B., and Thain, D. (2017). Deploying high throughput scientific workflows on container schedulers with makeflow and mesos. In CCGrid, CCGrid ’17, page 130–139. IEEE Press