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A broker-based framework for multi-cloud workflows

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Published:22 April 2013Publication History

ABSTRACT

Computational science workflows have been successfully run on traditional HPC systems like clusters and Grids for many years. Today, users are interested to execute their workflow applications in the Cloud to exploit the economic and technical benefits of this new emerging technology. The deployment and management of workflows over the current existing heterogeneous and not yet interoperable Cloud providers, however, is still a challenging task for the workflow developers. In this paper, we present a broker-based framework for running workflows in a multi-Cloud environment. The framework allows an automatic selection of the target Clouds, a uniform access to the Clouds, and workflow data management with respect to user Service Level Agreement (SLA) requirements. Following a simulation approach, we evaluated the framework with a real scientific workflow application in different deployment scenarios. The results show that our framework offers benefits to users by executing workflows with the expected performance and service quality at lowest cost.

References

  1. G. B. Berriman, E. Deelman, J. C. Good, J. C. Jacob, D. S. Katz, C. Kesselman, A. C. Laity, T. A. Prince, G. Singh, and M.-H. Su. Montage: a grid-enabled engine for delivering custom science-grade mosaics on demand. In Proceedings of the Society of Photo-Optical Instrumentation Engineers Conference, volume 5493 of SPIE 04, pages 221--232, September 2004.Google ScholarGoogle Scholar
  2. R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. F. D. Rose, and R. Buyya. 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, January 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. R. N. Calheiros, C. Vecchiola, D. Karunamoorthy, and R. Buyya. The Aneka platform and QoS-driven resource provisioning for elastic applications on hybrid Clouds. Future Generation Computer Systems, 28(6):861--870, June 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. W. Chen and E. Deelman. WorkflowSim: A Toolkit for Simulating Scientific Workflows in Distributed Environments. In Proceedings of the 8th IEEE International Conference on eScience, Chicago, USA, October 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. D. de Oliveira, E. Ogasawara, F. Baiao, and M. Mattoso. SciCumulus: A Lightweight Cloud Middleware to Explore Many Task Computing Paradigm in Scientific Workflows. In Proceedings of the 3rd IEEE International Conference on Cloud Computing, CLOUD '10, pages 378--385, Washington, DC, USA, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. E. Deelman, G. Juve, and G. B. Berriman. Using Clouds For Science, is it Just Kicking The Can Down the Road? In Proceedings of the International Conference on Cloud Computing and Services Science, CLOSER 2012, pages 127--133, Porto, Portugal, April 2012.Google ScholarGoogle Scholar
  7. B. Demuth, S. Bernd, H. Sonja, M. D. Jason, G. André, H. Valentina, and S. Sulev. The UNICORE Rich Client: Facilitating the Automated Execution of Scientific Workflows. In Proceedings of 6th IEEE International Conference on eScience, pages 238--245, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. J. O. Gutierrez-Garcia and K. M. Sim. Agent-based Cloud Workflow Execution. Integrated Computer-Aided Engineering, 19:39--56, 2012.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. M. Hardt, T. Jejkal, I. Campos, E. Fernandez, A. Jackson, D. Nielsson, B. Palak, and M. Plociennik. Transparent Access to Scientific and Commercial Clouds from the Kepler Workflow Engine. Computing and Informatics, 31:1001--1015, 2012.Google ScholarGoogle Scholar
  10. F. Jrad, J. Tao, R. Knapper, C. M. Flath, and A. Streit. A utility-based approach for customised cloud service selection. Int. J. Computational Science and Engineering, forthcoming.Google ScholarGoogle Scholar
  11. F. Jrad, J. Tao, and A. Streit. SLA Based Service Brokering in Intercloud Environments. In Proceedings of the International Conference on Cloud Computing and Services Science, CLOSER 2012, pages 76--81, Porto, Portugal, April 2012.Google ScholarGoogle Scholar
  12. G. Juve and E. Deelman. Scientific Workflows in the Cloud, pages 71--91. Computer Communications and Networks. Springer London, 2011.Google ScholarGoogle Scholar
  13. G. Juve, E. Deelman, G. Berriman, B. P. Berman, and P. Maechling. An Evaluation of the Cost and Performance of Scientific Workflows on Amazon EC2. Journal of Grid Computing, 10:5--21, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. S. Pandey, D. Karunamoorthy, and R. Buyya. Workflow Engine for Clouds, pages 321--344. John Wiley, Inc, 2011.Google ScholarGoogle Scholar
  15. I. Raicu, I. T. Foster, and Y. Zhao. Many-Task Computing for Grids and Supercomputers. In Proceedings of the IEEE Workshop on Many-Task Computing on Grids and Supercomputers, MTAGS 08, pages 1--11, Austin, TX, USA, November 2008.Google ScholarGoogle ScholarCross RefCross Ref
  16. J. Tao, D. Franz, H. Marten, and A. Streit. An Implementation Approach for Inter-Cloud Service Combination. International Journal on Advances in Software, 5:65--75, 2012.Google ScholarGoogle Scholar
  17. J. Yu and R. Buyya. A Taxonomy of Scientific Workflow Systems for Grid Computing. SIGMOD Rec., 34(3):44--49, September 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library

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            cover image ACM Conferences
            MultiCloud '13: Proceedings of the 2013 international workshop on Multi-cloud applications and federated clouds
            April 2013
            76 pages
            ISBN:9781450320504
            DOI:10.1145/2462326

            Copyright © 2013 ACM

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            New York, NY, United States

            Publication History

            • Published: 22 April 2013

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            MultiCloud '13 Paper Acceptance Rate9of18submissions,50%Overall Acceptance Rate9of18submissions,50%

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