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Reseach Article

An Evolutionary Study of Multi-Objective Workflow Scheduling in Cloud Computing

by Shashank Shukla, Anil Kumar Gupta, Sandeep Saxena, Santosh Kumar Upadhyay
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 133 - Number 14
Year of Publication: 2016
Authors: Shashank Shukla, Anil Kumar Gupta, Sandeep Saxena, Santosh Kumar Upadhyay
10.5120/ijca2016908109

Shashank Shukla, Anil Kumar Gupta, Sandeep Saxena, Santosh Kumar Upadhyay . An Evolutionary Study of Multi-Objective Workflow Scheduling in Cloud Computing. International Journal of Computer Applications. 133, 14 ( January 2016), 14-18. DOI=10.5120/ijca2016908109

@article{ 10.5120/ijca2016908109,
author = { Shashank Shukla, Anil Kumar Gupta, Sandeep Saxena, Santosh Kumar Upadhyay },
title = { An Evolutionary Study of Multi-Objective Workflow Scheduling in Cloud Computing },
journal = { International Journal of Computer Applications },
issue_date = { January 2016 },
volume = { 133 },
number = { 14 },
month = { January },
year = { 2016 },
issn = { 0975-8887 },
pages = { 14-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume133/number14/23854-2016908109/ },
doi = { 10.5120/ijca2016908109 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:31:12.602649+05:30
%A Shashank Shukla
%A Anil Kumar Gupta
%A Sandeep Saxena
%A Santosh Kumar Upadhyay
%T An Evolutionary Study of Multi-Objective Workflow Scheduling in Cloud Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 133
%N 14
%P 14-18
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud computing become more popular in every field of life nowadays. This happened only due to its amazing services that provide to clients in the form of everything-as-a-service(XaaS). Where at one side cloud computing is gaining popularity and another side its faces some issues i.e. security issue, total cost issue, energy consumption issue, performance issue, QoS issue, etc. In above all challenges the quality of services is the most noticeable challenge and affects the cloud computing services. Quality of services can be improved by considering the several factors, scheduling of workload for suitable cloud computing resources one of them. If the cloud computing resources are scheduled accurately, it affects the response time of services, total cost of cloud resources, reduce the energy consumption, reduce the CO2 emission and enhance the performance of whole cloud system. In this paper, we characterize a comparative review of multi-objective workflow scheduling algorithms that are listed below.

References
  1. RituGarg, Awadhesh Kumar Singh “Multi-Objective Optimization to Workflow Grid Scheduling using Reference Point based Evolutionary Algorithm" in International Journal of Computer Applications (0975 – 8887) Volume 22 – No.6, May 2011.
  2. Juan J. Durillo, RaduProdan" Multi-objective workflow scheduling in Amazon EC2 " in Springer June 2014, Volume 17, Issue 2, pp 169-189
  3. Sonia Yassa, Rachid Chelouah, Hubert Kadima, and Bertrand Granado" Multi-Objective Approach for Energy-Aware Workflow Scheduling in Cloud Computing Environments "in Scientific World Journal. 2013; 2013: 350934
  4. Topcuoglu, Haluk; Hariri, Salim Wu, M. (2002). "Performance-effective and low-complexity task scheduling for heterogeneous computing". IEEE Transactions on Parallel and Distributed Systems 13 (3): 260–274.
  5. Sanjaya K. Panda1, IEEE Member, Prasanta K. Jana2, IEEE Senior Member " A Multi-Objective Task Scheduling Algorithm for Heterogeneous Multi-Cloud Environment "in Electronic Design, Computer Networks & Automated Verification (EDCAV), 2015 International Conference on.
  6. J. Li, M. Qiu, Z. Ming, G. Quan, X. Qin and Z. Gu, “Online Optimization for Scheduling Pre-emptable Tasks on IaaS Cloud System”,Journal of Parallel Distributed Computing, Elsevier, Vol. 72, pp. 666-677, 2012.
  7. Atul Vikas Lakraa, Dharmendra Kumar Yadav "Multi-Objective Tasks Scheduling Algorithm for Cloud Computing Throughput Optimization"
  8. MengXu, Lizhen Cui, Haiyang Wang, Yanbing Bi A Multiple QoS Constrained Scheduling Strategy of Multiple Workflows for Cloud Computing in 2009 IEEE International Symposium on Parallel and Distributed Processing with Applications
  9. Jia Yu, RajkumarBuyya and Chen KhongTham, “Cost-basedScheduling of Scientific Workflow Applications on Utility Grids”, In 1st IEEE International Conference on e-Science and GridComputing, Melbourne, Australia, Dec. 5-8, 2005.
  10. Ke Liu, Jinjun Chen, Yun Yang and Hai Jin, “sA throughput maximization strategy for scheduling transaction-intensiveworkflows on SwinDeW-G”, Concurrency and Computation: Practice and Experience, Wiley, 20(15):1807-1820, Oct. 2008.
  11. Claudia Szabo, Trent Kroeger " Evolving Multi-objective Strategies for Task Allocation of Scientific Workflows on Public Clouds " in WCCI 2012 IEEE World Congress on Computational Intelligence June, 10-15, 2012 - Brisbane, Australia
  12. Anil Kumar Gupta, Shashank Shukla, Sandeep Saxena, Sanjay Khakhil “A Journey Towards Workflow Scheduling of Cloud Computing" in International Journal of Computer Applications (0975 – 8887) Volume 123 – No.4, August 2015
  13. R.T. Marler and J.S. Arora, “Survey of multi-objective optimization methods in engineering,” Structural and Multidisciplinary Optimization, Vol. 26, No. 6, pp. 369-395, April 2004.
  14. T. Fahringer, R. Prodan, R. Duan, F. Nerieri, S. Podlipnig, J. Qin, M. Siddiqui, H. L. Truong, A. Villaz´on, and M. Wieczorek, “Askalon: a grid application development and computing environment,” in 6th IEEE/ACM International Conference on Grid Computing, pp. 122–131, November 13-14, 2005.
  15. Fan Zhanga,b, JunweiCaob, Keqin Li, Samee U. Khand, Kai Hwange, “Multi-objective scheduling of many tasks in cloud platforms" in Future Generation Computer Systems 37 (2014) 309–320.
  16. Y.C. Ho, R. Sreenivas, P. Vaklili, Ordinal optimization of discrete event dynamic systems, Journal of Discrete Event Dynamic Systems 2 (2) (1992) 61–88.
  17. Y.C. Ho, Q.C. Zhao, Q.S. Jia, Ordinal Optimization, Soft Optimization for Hard Problems, Springer, 2007.
  18. Juan J. Durillo and VladNae and Radu Prodan "Multi-Objective Workflow Scheduling: An Analysis of the Energy Efficiency and Makespan Tradeoff" in 2013 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing.
  19. H. Topcuoglu, S. Hariri, and M.-Y. Wu, “Performance effective and low-complexity task scheduling for heterogeneous computing,” Parallel and Distributed Systems, IEEE Trans. on, vol. 13, no. 3, pp. 260 –274, mar 2002.
  20. M. Mezmaz, N. Melab, Y. Kessaci, Y. Lee, E.-G. Talbi, A.Y.Zomaya, and D. Tuyttens, “A parallel bi-objective hybrid metaheuristic for energy-aware scheduling for cloud computing systems,” Journal of Parallel and Distributed Computing, no. 71, pp. 1497–1508, 2011.
  21. J. Kolodziej, S. U. Khan, and F. Xhafa, “Genetic algorithms for energy-aware scheduling in computational grids,” in 2011Int. . Conf. on P2P, Parallel, Grid, Cloud and Int. et Computing, 2011.
  22. Hamid Mohammadi Fard, RaduProdan, Juan Jose Durillo Barrionuevo and Thomas Fahringer, “A Multi-Objective Approach for Workflow Scheduling in Heterogeneous Environments " in 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.
  23. Paul Rani, M.Gomathy Nayagam, “Multi-objective Qos Optimization Based on Multiple Workflow Scheduling in Cloud" in International Journal of Innovative Research in Computer and Communication Engineering Vol. 1, Issue 2, April 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Cloud computing multi-cloud computing Grid-Computing Multi-Objective workflow scheduling workflow scheduling and QoS.