Modelling and simulation of relationships between computational tasks in cloud environment
Abstract
Cloud computing enabled computational loads composed by dependent tasks, in a workflow structure. These dependence relationships demand specific characteristics in the resource management algorithms, which efficiency can be evaluated through simulation. However, the simulators normally used to test such methods, either do not support the workflow modeling, or require knowledge of some programming language from their user. Thus, it is proposed in this work a simple and robust graphic approach to model interdependencies between tasks.
Keywords:
workflow, simulation, cloud, distributed systems
References
Bolognesi, T. and Brinksma, E. (1987). Introduction to the iso specification language lotos.Computer Networks and ISDN systems, 14(1):25–59.
Calheiros, R. N., Ranjan, R., Beloglazov, A., Rose, C. A. D., and Buyya, R. (2011). Cloudsim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and Experience, 41(1):23–50.
Manacero, A., Lobato, R. S., Oliveira, P. H., Garcia, M. A., Guerra, A. I., Aoqui, V., Menezes, D., and Da Silva, D. T. (2012). iSPD: an iconic-based modeling simulator for distributed grids. InProceedings of the 45th Annual Simulation Symposium, page 5. Society for Computer Simulation International.
Ramakrishnan, A., Singh, G., Zhao, H., Deelman, E., Sakellariou, R., Vahi, K., Blackburn, K., Meyers, D., and Samidi, M. (2007). Scheduling data-intensive workflows onto storage-constrained distributed resources. InSeventh IEEE International Symposiumon Cluster Computing and the Grid (CCGrid’07), pages 401–409. IEEE.
Satish, N. R., Ravindran, K., and Keutzer, K. (2008). Scheduling task dependence graphs with variable task execution times onto heterogeneous multiprocessors. InProceedings of the 8th ACM international conference on Embedded software, pages 149–158. ACM.
Tick, J. (2006). Workflow model representation concepts. In Proceedings of 7th International Symposium of Hungarian Researchers on Computational Intelligence, HUCI, pages 24–25.
Calheiros, R. N., Ranjan, R., Beloglazov, A., Rose, C. A. D., and Buyya, R. (2011). Cloudsim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and Experience, 41(1):23–50.
Manacero, A., Lobato, R. S., Oliveira, P. H., Garcia, M. A., Guerra, A. I., Aoqui, V., Menezes, D., and Da Silva, D. T. (2012). iSPD: an iconic-based modeling simulator for distributed grids. InProceedings of the 45th Annual Simulation Symposium, page 5. Society for Computer Simulation International.
Ramakrishnan, A., Singh, G., Zhao, H., Deelman, E., Sakellariou, R., Vahi, K., Blackburn, K., Meyers, D., and Samidi, M. (2007). Scheduling data-intensive workflows onto storage-constrained distributed resources. InSeventh IEEE International Symposiumon Cluster Computing and the Grid (CCGrid’07), pages 401–409. IEEE.
Satish, N. R., Ravindran, K., and Keutzer, K. (2008). Scheduling task dependence graphs with variable task execution times onto heterogeneous multiprocessors. InProceedings of the 8th ACM international conference on Embedded software, pages 149–158. ACM.
Tick, J. (2006). Workflow model representation concepts. In Proceedings of 7th International Symposium of Hungarian Researchers on Computational Intelligence, HUCI, pages 24–25.
Published
2020-08-19
How to Cite
BALDISSERA, Luís Vinícius; MANACERO JR., Aleardo; LOBATO, Renata Spolon; SPOLON, Roberta.
Modelling and simulation of relationships between computational tasks in cloud environment. In: REGIONAL SCHOOL OF HIGH PERFORMANCE COMPUTING FROM SÃO PAULO (ERAD-SP), 11. , 2020, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 18-21.
DOI: https://doi.org/10.5753/eradsp.2020.16876.
