Resource Utilization of Workflow Scheduling Algorithms in Public Cloud

Authors

  • Dr. T. Lucia Agnes Beena  Assistant Professor and Head, Department of Information Technology, St. Joseph's College, Triuchirappalli, Tamil Nadu, India

Keywords:

Cloud Computing, Resource Utilization, Tasks Scheduling, Workflow Scheduling

Abstract

The advent of Web 2.0 and Internet, transform the Grid Computing to Cloud Computing. The growing reputation of cloud computing has fascinated many IT organizations to move towards the Cloud which widens the Cloud Data centers. The raise in number of Data centers influence the need for the energy efficiency in Cloud. The energy efficiency can be achieved through energy-aware resource management, development of efficient policies and algorithms for virtualized data centers and eco-friendly technology. This paper focuses the resource utilization parameter of the resource management by efficient mapping of applications to Cloud resources. The algorithms discussed in this paper reduce the application execution time by assigning the appropriate resources, there by maximizing the resource utilization. Among the various algorithms discussed, Differential Evolution Algorithm for Workflow Scheduling in Public Cloud outstrips the other algorithms in minimizing the execution time of the application, minimizing the cost of executing the application and maximizing the resource utilization.

References

  1. Buyya R, Beloglazov A, Abawajy J., “Energy-efficient management of data center resources for cloud computing: a vision, architectural elements, and open challenges”, arXiv preprint arXiv:1006.0308, 2010.
  2. George Amalarethinam D. I., Lucia Agnes Beena T., “Customer Facilitated Cost-based Scheduling algorithm (CFCSC) in Cloud”, Procedia Computer Science, Elsevier Publications 46C, pp. 660-667, April 2015.
  3. George Amalarethinam D. I., Lucia Agnes Beena T., “Level Based Task Prioritization Scheduling for Small Workflows in Cloud Environment”, Indian Journal of Science and Technology, Vol. 8, Issue 33, pp 1–7, 2015.
  4. George Amalarethinam D. I., Lucia Agnes Beena T., “Workflow Scheduling for Public Cloud using Genetic Algorithm (WSGA)”, IOSR Journal of Computer Engineering (IOSR-JCE), 18(3), V, 23-27, May-Jun. 2016.
  5. George Amalarethinam D. I., Lucia Agnes Beena T., “Differential Evolution Algorithm for Workflow Scheduling (DEWS) in Public Cloud”, International Journal of Control Theory and Applications, Vol. 9, No. 27, pp. 43 – 50, ISSN No:0974-5572, Oct 2016.
  6. Lee, Young Choon, and Albert Y. Zomaya. "Energy efficient utilization of resources in cloud computing systems." The Journal of Supercomputing, Vol. 60, Issue 2, pp. 268-280, 2012.
  7. Sindhu, S., and Saswati Mukherjee., "Efficient task scheduling algorithms for cloud computing environment.", High Performance Architecture and Grid Computing, pp. 79-83, 2011.
  8. Beloglazov, Anton, and Rajkumar Buyya. "Energy efficient resource management in virtualized cloud data centers." In Proceedings of the 2010 10th IEEE/ACM international conference on cluster, cloud and grid computing, IEEE Computer Society, pp. 826-831, 2010.
  9. Shakkeera, L., Latha Tamilselvan, and Mohamed Imran. "Improving Resource Utilization Using Qos Based Load Balancing Algorithm For Multiple Workflows In Iaas Cloud Computing Environment.", ICTACT Journal on Communication Technology 4, Vol. 02, 750-757, 2013.
  10. Beloglazov, Anton, Jemal Abawajy, and Rajkumar Buyya. "Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing.", Future generation computer systems, Vol.28, Issue 5, pp. 755-768, 2012.
  11. Gaojin Wen, Jue Hong, Chengzhong Xu, Pavan Balaji, Shengzhong Feng, Pingchuang Jiang, “Energy-aware Hierarchical Scheduling of Applications in Large Scale Data Centers”, International Conference on Cloud and Service Computing, IEEE Publications, pp. 158-165, 2011.
  12. Abrishami, S., Naghibzadeh, M., “Deadline-constrained workflow scheduling in software as a service Cloud”, Computer Science & Engineering and Electrical Engineering, Scientia Iranica, vol. 19, issue 3, pp. 680–689, 2012.
  13. Abazar Shamekhi, “An Improved Differential Evolution Optimization Algorithm”, International Journal of Research and Reviews in Applied Sciences, 15, 2013.
  14. George Amalarethinam D.I, Joyce Mary G. J. DAGEN – A tool to generate arbitrary Directed Acyclic Graphs used for Multiprocessor Scheduling. International Journal of Research and Reviews in Computer Science (IJRRCS), Vol. 2, Issue 3, pp. 782 – 787, 2011.

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2018-02-28

Issue

Volume 4, Issue 1, January-February-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dr. T. Lucia Agnes Beena, " Resource Utilization of Workflow Scheduling Algorithms in Public Cloud, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 1, pp.1649-1656, January-February-2018.