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Unified Multi-constraint and Multi-objective Workflow Scheduling for Cloud System

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Algorithms and Architectures for Parallel Processing (ICA3PP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9529))

Abstract

With the development of cloud computing, the problem of scheduling workflow in cloud system attracts a large amount of attention. In general, the cloud workflow scheduling problem requires to consider a variety of optimization objectives with some constraints. Traditional workflow scheduling methods focus on single optimization goal like makespan and single constraint like deadline or budget. In this paper, we first make a unified formalization of the optimality problem of multi-constraint and multi-objective cloud workflow scheduling using pareto optimality theory. We also present a two-constraint and two-objective case study, considering deadline, budget constraints and energy consumption, reliability objectives. A general list scheduling algorithm and a tuning mechanism are designed to solve this problem. Through extensive experimental, it confirms the efficiency of the unified multi-constraint and multi-objective cloud workflow scheduling system.

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References

  1. Kwok, Y.K., Ahmad, I.: Static scheduling algorithms for allocating directed task graphs to multiprocessors. ACM Comput. Surv. (CSUR) 31(4), 406–471 (1999)

    Article  Google Scholar 

  2. Yu, J., Buyya, R., Ramamohanarao, K.: Workflow scheduling algorithms for grid computing. In: Xhafa, F., Abraham, A. (eds.) Metaheuristics for Scheduling in Distributed Computing Environments. SCI, vol. 146, pp. 173–214. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  3. Yu, J., Buyya, R., Tham, C.K.: Cost-based scheduling of scientific workflow applications on utility grids. In: First International Conference on e-Science and Grid Computing, pp. 8–15 (2005)

    Google Scholar 

  4. Yuan, Y., Li, X., Wang, Q., Zhang, Y.: Bottom level based heuristic for workflow scheduling in Grids. Chin. J. Comput. 31(2), 282 (2008). Chinese Edition

    Article  Google Scholar 

  5. Yuan, Y., Li, X., Wang, Q., Zhu, X.: Deadline division-based heuristic for cost optimization in workflow scheduling. Inf. Sci. 179(15), 2562–2575 (2009)

    Article  MATH  Google Scholar 

  6. Abrishami, S., Naghibzadeh, M., Epema, D.H.: Deadline-constrained workflow scheduling algorithms for infrastructure as a service clouds. Future Gener. Comput. Syst. 29(1), 158–169 (2013)

    Article  Google Scholar 

  7. Yu, J., Ramamohanarao, K., Buyya, R.: Deadline/budget-based scheduling of workflows on utility grids. In: Market-Oriented Grid and Utility Computing, pp. 427–450 (2009)

    Google Scholar 

  8. Zheng, W., Sakellariou, R.: Budget-deadline constrained workflow planning for admission control. J. Grid Comput. 11(4), 633–651 (2013)

    Article  Google Scholar 

  9. Arabnejad, H., Barbosa, J.G.: A budget constrained scheduling algorithm for workflow applications. J. Grid Comput. 12(4), 665–679 (2014)

    Article  Google Scholar 

  10. Sakellariou, R., Zhao, H., Tsiakkouri, E., Dikaiakos, M.D.: Scheduling workflows with budget constraints. In: Integrated Research in Grid Computing, pp. 189–202 (2007)

    Google Scholar 

  11. Li, J., Su, S., Cheng, X., Huang, Q.J., Zhang, Z.B.: Cost-conscious scheduling for large graph processing in the cloud. In: IEEE 13th International Conference on High Performance Computing and Communications (HPCC), pp. 808–813 (2011)

    Google Scholar 

  12. Garg, S.K., Buyya, R., Siegel, H.J.: Time and cost trade-off management for scheduling parallel applications on utility grids. Future Gener. Comput. Syst. 26(8), 1344–1355 (2010)

    Article  Google Scholar 

  13. Fard, H.M., Prodan, R., Barrionuevo, J.J D., Fahringer, T.: A multi-objective approach for workflow scheduling in heterogeneous environments. In: Proceedings of the 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID 2012), pp. 300–309 (2012)

    Google Scholar 

  14. Marler, R.T., Arora, J.S.: Survey of multi-objective optimization methods in engineering. Struct. Multi. Optim. 26(6), 369–395 (2004)

    Article  MATH  Google Scholar 

  15. Dogan, A., Ozguner, F.: Matching and scheduling algorithms for minimizing execution time and failure probability of applications in heterogeneous computing. IEEE Trans. Parallel Distrib. Syst. 13(3), 308–323 (2002)

    Article  Google Scholar 

  16. Wieczorek, M., Podlipnig, S., Prodan, R., Fahringer, T.: Bi-criteria scheduling of scientific workflows for the grid. In: IEEE 8th International Symposium on Cluster Computing and the Grid (CCGRID 2008), pp. 9–16 (2008)

    Google Scholar 

  17. Prodan, R., Wieczorek, M.: Bi-criteria scheduling of scientific grid workflows. IEEE Trans. Autom. Sci. Eng. 7(2), 364–376 (2010)

    Article  Google Scholar 

  18. Bessai, K., Youcef, S., Oulamara, A., Godart, C., Nurcan, S.: Bi-criteria workflow tasks allocation and scheduling in cloud computing environments. In: IEEE 5th International Conference on Cloud Computing (CLOUD), pp. 638–645 (2012)

    Google Scholar 

  19. Yu, J., Kirley, M., Buyya, R.: Multi-objective planning for workflow execution on grids. In: Proceedings of the 8th IEEE/ACM International Conference on Grid Computing, pp. 10–17 (2007)

    Google Scholar 

  20. Baskiyar, S., Abdel-Kader, R.: Energy aware DAG scheduling on heterogeneous systems. Cluster Comput. 13(4), 373–383 (2010)

    Article  Google Scholar 

  21. Cao, F., Zhu, M.M., Wu, C.Q.: Energy-efficient resource management for scientific workflows in clouds. In: IEEE World Congress on Services (SERVICES), pp. 402–409. IEEE (2014)

    Google Scholar 

  22. Lee, Y.C., Zomaya, A.Y.: Energy conscious scheduling for distributed computing systems under different operating conditions. IEEE Trans. Parallel Distrib. Syst. 22(8), 1374–1381 (2011)

    Article  Google Scholar 

  23. Mezmaz, M., Melab, N., Kessaci, Y., Lee, Y.C., Talbi, E.G., Zomaya, A.Y., Tuyttens, D.: A parallel bi-objective hybrid metaheuristic for energy-aware scheduling for cloud computing systems. J. Parallel Distrib. Comput. 71(11), 1497–1508 (2011)

    Article  Google Scholar 

  24. Yassa, S., Chelouah, R., Kadima, H., Granado, B.: Multi-objective approach for energy-aware workflow scheduling in cloud computing environments. Sci. World J. (2013)

    Google Scholar 

  25. Poola, D., Ramamohanarao, K., Buyya, R.: Fault-tolerantworkflowscheduling using spot instances on clouds. Procedia Comput Sci. 29, 523–533 (2014)

    Article  Google Scholar 

  26. Fard, H.M., Prodan, R., Barrionuevo, J.J.D., Fahringer, T.: A multi-objective approach for workflow scheduling in heterogeneous environments. In: 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 300–309 (2012)

    Google Scholar 

  27. Topcuoglu, H., Hariri, S., Wu, M.Y.: Performance-effective and low-complexity task scheduling for heterogeneous computing. IEEE Trans. Parallel Distrib. Syst. 13(3), 260–274 (2002)

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Computer Science, National University of Defense Technology, Changsha, 410073, China

    Fuhui Wu, Qingbo Wu, Yusong Tan & Wei Wang

Authors
  1. Fuhui Wu
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  2. Qingbo Wu
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  3. Yusong Tan
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  4. Wei Wang
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Corresponding author

Correspondence to Fuhui Wu .

Editor information

Editors and Affiliations

  1. Central South University, Changsha, China

    Guojun Wang

  2. The University of Sydney, Sydney, New South Wales, Australia

    Albert Zomaya

  3. University of Murcia, Murcia, Murcia, Spain

    Gregorio Martinez

  4. Hunan University , Changsha, China

    Kenli Li

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© 2015 Springer International Publishing Switzerland

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Wu, F., Wu, Q., Tan, Y., Wang, W. (2015). Unified Multi-constraint and Multi-objective Workflow Scheduling for Cloud System. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9529. Springer, Cham. https://doi.org/10.1007/978-3-319-27122-4_44

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  • DOI: https://doi.org/10.1007/978-3-319-27122-4_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27121-7

  • Online ISBN: 978-3-319-27122-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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