The week's pick
Reseach Article
Improving Max-Min scheduling Algorithm for Reducing the Makespan of Workflow Execution in the Cloud
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 177 - Number 3 |
| Year of Publication: 2017 |
| Authors: Ali S. A. Al-Haboobi |
10.5120/ijca2017915684
|
Ali S. A. Al-Haboobi . Improving Max-Min scheduling Algorithm for Reducing the Makespan of Workflow Execution in the Cloud. International Journal of Computer Applications. 177, 3 ( Nov 2017), 5-9. DOI=10.5120/ijca2017915684
Abstract
Cloud computing has become a new paradigm that provides IT resources as a service based on the basis: pay-per-use over the internet. Scientific workflow applications can gain the advantage by running on cloud resources. However, the optimized of workflow scheduling algorithms is a challenge and still needed further work. This paper presents an improved Max-Min algorithm based on the Max-Min algorithm. It can minimize the makespan of workflow execution and increases the resource utilization. The algorithm tested using WorkflowSim with five workflows from the Pegasus workflow management system. The results show that this algorithm can achieve better than Max-Min in most of the cases.
References
- R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, "Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility," Future Gener. Comput. Syst., vol. 25, pp. 599-616, 2009.
- E. Deelman, D. Gannon, M. Shields, and I. Taylor, "Workflows and e-Science: An overview of workflow system features and capabilities," Future Gener. Comput. Syst., vol. 25, pp. 528-540, 2009.
- S. Bharathi, A. Chervenak, E. Deelman, G. Mehta, M. H. Su, and K. Vahi, "Characterization of scientific workflows," in 2008 Third Workshop on Workflows in Support of Large-Scale Science, 2008, pp. 1-10.
- A. Abraham, R. Buyya, and B. Nath, "Nature’s heuristics for scheduling jobs on computational grids," in The 8th IEEE international conference on advanced computing and communications (ADCOM 2000), 2000, pp. 45-52.
- H. Topcuoglu, S. Hariri, and W. Min-You, "Performance-effective and low-complexity task scheduling for heterogeneous computing," IEEE Transactions on Parallel and Distributed Systems, vol. 13, pp. 260-274, 2002.
- J. D. Ullman, "NP-complete scheduling problems," J. Comput. Syst. Sci., vol. 10, pp. 384-393, 1975.
- F. Dong and S. G. Akl, "Scheduling algorithms for grid computing: State of the art and open problems," Technical report2006.
- S. Parsa and R. Entezari-Maleki, "RASA: A new task scheduling algorithm in grid environment," World Applied sciences journal, vol. 7, pp. 152-160, 2009.
- U. Bhoi and P. N. Ramanuj, "Enhanced max-min task scheduling algorithm in cloud computing," International Journal of Application or Innovation in Engineering and Management (IJAIEM), vol. 2, pp. 259-264, 2013.
- W. Sun, N. Zhang, H. Wang, W. Yin, and T. Qiu, "PACO: A period ACO based scheduling algorithm in cloud computing," in Cloud Computing and Big Data (CloudCom-Asia), 2013 International Conference on, 2013, pp. 482-486.
- G. Ming and H. Li, "An Improved Algorithm Based on Max-Min for Cloud Task Scheduling," in Recent Advances in Computer Science and Information Engineering: Volume 2, Z. Qian, L. Cao, W. Su, T. Wang, and H. Yang, Eds., ed Berlin, Heidelberg: Springer Berlin Heidelberg, 2012, pp. 217-223.
- W. Chen and E. Deelman, "Workflowsim: A toolkit for simulating scientific workflows in distributed environments," in E-Science (e-Science), 2012 IEEE 8th International Conference on, 2012, pp. 1-8.
- R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. De 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, vol. 41, pp. 23-50, 2011.
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