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Reseach Article

A Journey towards Workflow Scheduling of Cloud Computing

by Anil Kumar Gupta, Shashank Shukla, Sandeep Saxena, Sanjay Khakhil
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 123 - Number 4
Year of Publication: 2015
Authors: Anil Kumar Gupta, Shashank Shukla, Sandeep Saxena, Sanjay Khakhil
10.5120/ijca2015905219

Anil Kumar Gupta, Shashank Shukla, Sandeep Saxena, Sanjay Khakhil . A Journey towards Workflow Scheduling of Cloud Computing. International Journal of Computer Applications. 123, 4 ( August 2015), 5-9. DOI=10.5120/ijca2015905219

@article{ 10.5120/ijca2015905219,
author = { Anil Kumar Gupta, Shashank Shukla, Sandeep Saxena, Sanjay Khakhil },
title = { A Journey towards Workflow Scheduling of Cloud Computing },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 123 },
number = { 4 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 5-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume123/number4/21945-2015905219/ },
doi = { 10.5120/ijca2015905219 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:11:44.854514+05:30
%A Anil Kumar Gupta
%A Shashank Shukla
%A Sandeep Saxena
%A Sanjay Khakhil
%T A Journey towards Workflow Scheduling of Cloud Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 123
%N 4
%P 5-9
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud computing is a type of grid computing which is a form of distributed computing and distributed computing is a special type of parallel computing. Presently a lot of services are growing under the single umbrella that is known as cloud computing. Cloud computing gain popularity in the several area due its property of everything-as -a-service( XaaS), includes SaaS, PaaS and IaaS. Many problems have been arising when we go for implementation development. Workflow scheduling and appropriate allocation of resources is one of among problems that will decrease the Quality of Service (QoS) of cloud computing. There are many algorithms to automate the workflows in a way to satisfy the Quality of service (QoS) of the user. This paper is the survey of some workflow scheduling algorithms that have been proposed for cloud computing.

References
  1. Quality-of-service in cloud computing: modeling techniques and their applications Danilo Ardagna, Giuliano Casale, Michele Ciavotta, JuaJuann F Pérezand Weikun Wang in 2014.
  2. Ardagna D, Panicucci B, Trubian M, Zhang L (2012) Energy-aware autonomic resource allocation in multitier virtualized environments. IEEE Trans Serv Comput 5(1):2-19
  3. A. Sulistio and R. Buyya, “A Grid Simulation Infrastructure Supporting Advance Reservation”, In 16th International Conference on Parallel and Distributed Computing and Systems (PDCS 2004), November 911, 2004, MIT Cambridge, Boston, USA.
  4. L. F. Bittencourt and E. R. M. Madeira, “A performance-oriented adaptive scheduler for dependent tasks on grids,” Concurrency and Computation: Practice and Experience, vol. 20, no. 9, pp. 1029–1049, 2008.
  5. An Approach to Workflow Scheduling using Priority in Cloud Computing Environment P. Kumar, V. Anandarangan and A. Reshma in International Journal of Computer Applications (0975 – 8887) Volume 109 – No. 11, January 2015
  6. Advance Reservation of Resources in Workflow System, Lalit et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.12, December- 2014, pg. 140-145
  7. A Survey of Workflow Scheduling Algorithms and Research Issues in International Journal of Computer Applications (0975 – 8887) Volume 74– No.15, July 2013.
  8. Jia Yu, Rajkumar Buyyaand Chen Khong Tham in Proceedings of the First International Conference on e-Science and Grid Computing (e-Science’05) 0-7695-2448-6/05 $20.00 © 2005 IEEE.
  9. R. Buyya, J. Giddy, and D. Abramson, “An Evaluation of Economy based Resource Trading and Scheduling on Computational Power Grids for Parameter Sweep Applications”, In 2nd Workshop on Active Middleware Services (AMS 2000), Kluwer Academic Press, August 1, 2000, Pittsburgh, USA.
  10. A. Geppert, M. Kradolfer, and D. Tombros, “Market-based Workflow Management”, International Journal of Cooperative Information Systems, World Scientific Publishing Co., NJ, USA, 1998.
  11. Meng Xu, Lizhen Cui, Haiyang Wang, Yanbing Bi A Multiple QoS Constrained Scheduling Strategy of Multiple Workflows for CloudComputing in 2009 IEEE International Symposium on Parallel and Distributed Processing with Applications
  12. Jia Yu, Rajkumar Buyya and Chen Khong Tham, “Cost-basedScheduling of Scientific Workflow Applications on Utility Grids”, In1st IEEE International Conference on e-Science and GridComputing, Melbourne, Australia, Dec. 5-8, 2005.
  13. Ke Liu, Jinjun Chen, Yun Yang and Hai Jin, “A throughputmaximization strategy for scheduling transaction-intensiveworkflows on SwinDeW-G”, Concurrency and Computation:Practice and Experience, Wiley, 20(15):1807-1820, Oct. 2008.
  14. Scheduling Service Workflows for Cost Optimization in Hybrid Clouds by Luiz F. Bittencourt, Carlos R. Senna and Edmundo R. M. Madeira in 978-1-4244-8909-1/$26.00 2010 IEEE.
  15. Scheduling Scientific Workflows Elastically for Cloud Computing by Cui Lin and Shiyong Lu in 2011 IEEE 4th International Conference on Cloud Computing.
  16. Jignesh Lakhani and Hitesh Bheda,”Scheduling Technique of Data Intensive Application Workflows In Cloud Computing”Nirma University International Conference On Engineering, Nuicone-2012, 06-08december, 2012.
  17. Trust-based and QoS Demand Clustering Analysis Customizable Cloud Workflow Scheduling Strategies Wenjuan Li Qifei Zhang Jiyi Wu and Jing Li in 978-0-7695-4844-9/12 $26.00 © 2012 IEEE DOI 10.1109/ClusterW.2012.21 in 2012 IEEE International Conference on Cluster Computing Workshops.
  18. Peng Liu.: Cloud Computing, Second Editon [M]. Beijing: Publishing House of Electronics Industry, 2011.
  19. Hamid MohammadiFard, RaduProdan, and Thomas Fahringer, “A Truthful Dynamic Workflow Scheduling Mechanism for Commercial Multicloud Environments,” in IEEE Transactions on Parallel and Distributed Systems, VOL. 24, NO. 6, JUNE 2013.
  20. A. Archer and E. Tardos, “Truthful Mechanisms for One-Parameter Agents,” Proc. 42nd IEEE Symp. Foundations of Computer Science, pp. 482-491, 2001.
  21. N. Nisan, T. Roughgarden, E. Tardos, and V. Vazirani,” AlgorithmicGame Theory,”Cambridge Univ. Press, 2007.
  22. Fei Cao and Michelle M. Zhu ,”Energy Efficient Workflow Job Scheduling for Green Cloud” in IEEE 27th International Symposium on Parallel & Distributed Processing Workshops and PhD Forum, 2013.
  23. Maria Alejandra Rodriguez and Rajkumar Buyya, “Deadline Based Resource Provisioning and Scheduling Algorithm for Scientific Workflows on Clouds” in IEEE Transactions On Cloud Computing, Vol.2, No.2, April-June 2014 2168-7161 2
  24. Cluster based Scheduling of Workflow Applications in Cloud Ardra V A and Sindhu S in International Journal of Computer Applications (0975 – 8887) Advanced Computing and Communication Techniques for High Performance Applications (ICACCTHPA-2014)
Index Terms

Computer Science
Information Sciences

Keywords

Cloud computing grid computing distributed computing parallel computing workflow scheduling Virtualization and QoS.