Predição de Falhas em Workflows Científicos com o uso de Redes de Petri Estocásticas e Lógica DS
Resumo
Vários workflows existentes exigem muitos recursos computacionais, pois processam um grande volume de dados. Dessa forma, os ambientes de Processamento de Alto Desempenho (PAD) devem ser aplicados em conjunto com técnicas de paralelização para apoiar a sua execução. Embora os ambientes de PAD ofereçam diversas vantagens, as falhas são uma realidade, e não uma possibilidade, devido ao grande número de nós de computação envolvidos na execução do workflow. Verificar falhas no workflow é uma tarefa desafiadora que ainda requer esforço. Neste artigo, propomos o uso da DS3, uma lógica dinâmica adaptada sobre as redes de Petri estocásticas, para verificar e prever falhas em workflows.
Referências
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Curcin, V., Ghanem, M. M., and Guo, Y. (2009). Analysing scientific workflows with Computational Tree Logic. Cluster Computing, 12(4):399–418.
de Oliveira, D., Oca˜na, K. A. C. S., Bai˜ao, F. A., and Mattoso, M. (2012). A provenance-based adaptive scheduling heuristic for parallel scientific workflows in clouds. J. Grid Comput., 10(3):521–552.
Deelman, E., Gannon, D., Shields, M., and Taylor, I. (2009). Workflows and e-science: An overview of workflow system features and capabilities. Future Generation Computer Systems, 25(5):528–540.
Freire, J., Koop, D., Santos, E., and Silva, C. T. (2008). Provenance for Computational Tasks: A Survey. Computing in Science & Engineering, pages 20–30.
Hofstede, A. H. M., Orlowska, M. E., and Rajapakse, J. (1998). Verification problems in conceptual workflow specifications. Data & Knowledge Engineering, 24(3):239–256.
Jacob, J. C., Katz, D. S., Berriman, G. B., Good, J., Laity, A. C., Deelman, E., Kesselman, C., Singh, G., Su, M.-H., Prince, T. A., et al. (2010). Montage: An astronomical image
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Juve, G., Chervenak, A. L., Deelman, E., Bharathi, S., Mehta, G., and Vahi, K. (2013). Characterizing and profiling scientific workflows. Future Generation Comp. Syst., 29(3):682–692.
Liang, Q. A. and Zhao, J. L. (2008). Verification of unstructured workflows via propositional logic. In Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008), pages 247–252.
Liu, J., Pacitti, E., Valduriez, P., and Mattoso, M. (2015). A survey of data-intensive scientific workflow management. Journal of Grid Computing, 13(4):457–493.
Lopes, B., Benevides, M., and Haeusler, E. H. (2014). Extending Propositional Dynamic Logic for Petri Nets. Elec. Notes in Theo. Comp. Science, 305(11):67–83.
Marsan, M. A. (1990). Stochastic Petri Nets: An elementary introduction. In Rozenberg, G., editor, Advances in Petri Nets 1989, volume 424 of LNCS, pages 1–29. Springer.
Marsan, M. A. and Chiola, G. (1987). On Petri Nets with deterministic and exponentially distributed firing times. In Advances in Petri Nets 1987, pages 132–145. Springer.
Ogasawara, E., Dias, J., Oliveira, D., Porto, F., Valduriez, P., and Mattoso, M. (2011). An algebraic approach for data-centric scientific workflows. PVLDB, 4(12):1328–1339.
Salimifard, K. and Wright, M. (2001). Petri net-based modelling of workflow systems: An overview. European Journal of Operational Research, 134(3):664–676.
van der Aalst, W. M. P. (1998). The application of Petri nets to workflow management. Journal of Circuits, Systems, and Computers, 8(1):21–66.
Zhao, L., Li, Q., Liu, X., and Du, N. (2009). A modeling method based on ccs for workflow. In Proceedings of ICUIMC’09, pages 376–384.
Curcin, V., Ghanem, M. M., and Guo, Y. (2009). Analysing scientific workflows with Computational Tree Logic. Cluster Computing, 12(4):399–418.
de Oliveira, D., Oca˜na, K. A. C. S., Bai˜ao, F. A., and Mattoso, M. (2012). A provenance-based adaptive scheduling heuristic for parallel scientific workflows in clouds. J. Grid Comput., 10(3):521–552.
Deelman, E., Gannon, D., Shields, M., and Taylor, I. (2009). Workflows and e-science: An overview of workflow system features and capabilities. Future Generation Computer Systems, 25(5):528–540.
Freire, J., Koop, D., Santos, E., and Silva, C. T. (2008). Provenance for Computational Tasks: A Survey. Computing in Science & Engineering, pages 20–30.
Hofstede, A. H. M., Orlowska, M. E., and Rajapakse, J. (1998). Verification problems in conceptual workflow specifications. Data & Knowledge Engineering, 24(3):239–256.
Jacob, J. C., Katz, D. S., Berriman, G. B., Good, J., Laity, A. C., Deelman, E., Kesselman, C., Singh, G., Su, M.-H., Prince, T. A., et al. (2010). Montage: An astronomical image
mosaicking toolkit. 1:10036.
Juve, G., Chervenak, A. L., Deelman, E., Bharathi, S., Mehta, G., and Vahi, K. (2013). Characterizing and profiling scientific workflows. Future Generation Comp. Syst., 29(3):682–692.
Liang, Q. A. and Zhao, J. L. (2008). Verification of unstructured workflows via propositional logic. In Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008), pages 247–252.
Liu, J., Pacitti, E., Valduriez, P., and Mattoso, M. (2015). A survey of data-intensive scientific workflow management. Journal of Grid Computing, 13(4):457–493.
Lopes, B., Benevides, M., and Haeusler, E. H. (2014). Extending Propositional Dynamic Logic for Petri Nets. Elec. Notes in Theo. Comp. Science, 305(11):67–83.
Marsan, M. A. (1990). Stochastic Petri Nets: An elementary introduction. In Rozenberg, G., editor, Advances in Petri Nets 1989, volume 424 of LNCS, pages 1–29. Springer.
Marsan, M. A. and Chiola, G. (1987). On Petri Nets with deterministic and exponentially distributed firing times. In Advances in Petri Nets 1987, pages 132–145. Springer.
Ogasawara, E., Dias, J., Oliveira, D., Porto, F., Valduriez, P., and Mattoso, M. (2011). An algebraic approach for data-centric scientific workflows. PVLDB, 4(12):1328–1339.
Salimifard, K. and Wright, M. (2001). Petri net-based modelling of workflow systems: An overview. European Journal of Operational Research, 134(3):664–676.
van der Aalst, W. M. P. (1998). The application of Petri nets to workflow management. Journal of Circuits, Systems, and Computers, 8(1):21–66.
Zhao, L., Li, Q., Liu, X., and Du, N. (2009). A modeling method based on ccs for workflow. In Proceedings of ICUIMC’09, pages 376–384.
Publicado
24/06/2019
Como Citar
LOPES, Bruno; DE OLIVEIRA, Daniel.
Predição de Falhas em Workflows Científicos com o uso de Redes de Petri Estocásticas e Lógica DS. In: BRAZILIAN E-SCIENCE WORKSHOP (BRESCI), 13. , 2019, Belém.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
ISSN 2763-8774.
DOI: https://doi.org/10.5753/bresci.2019.10027.
