Child based Level-Wise List Scheduling Algorithm

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Author(s)

Lokesh Kr. Arya 1,* Amandeep Verma 1

1. University Institute of Engg. & Technology, Panjab University, Chandigarh, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2017.09.03

Received: 25 Mar. 2016 / Revised: 23 May 2016 / Accepted: 22 Aug. 2017 / Published: 8 Sep. 2017

Index Terms

Workflows, Scheduling Algorithms, Cloud Scheduling, Cloud Computing, Task Scheduling, Schedule length, Makespan.

Abstract

Cloud is the Latest concept in IT. Users use the resources or services which are provided & managed by the service providers. Users need not to buy the hardware or software which now can be used on rental basis. Workflow represents the cloud application which has different tasks to be executed in an order. Scheduling algorithms are used to assign these tasks to processors and these algorithms decide the cost and time of execution. In this paper, a simple scheduling algorithm has been proposed named Child Based Level-Wise List Scheduling (CBLWLS) algorithm. According to the dependencies CBLWSL calculate priorities of tasks and finds the sequence of task execution and then maps the selected task to the available processors. We perform experiments on Epigenomics workflow structure graphs used in some real applications and their analysis shows that CBLWLS algorithm performed better than the HEFT (Heterogeneous Earliest Finish Time) algorithm, on the parameters of time of execution, execution cost and schedule length ratio.

Cite This Paper

Lokesh Kr. Arya, Amandeep Verma, " Child based Level-Wise List Scheduling Algorithm", International Journal of Modern Education and Computer Science(IJMECS), Vol.9, No.9, pp. 24-31, 2017. DOI:10.5815/ijmecs.2017.09.03

Reference

[1]L. K. Arya and A. Verma, “Workflow scheduling algorithms in cloud environment - A survey”, RAECS, March 2014, IEEE, 1-4.
[2]Md. Imran Alam, Manjusha Pandey, Siddharth S Rautaray, “A Comprehensive Survey on Cloud Computing”, IJITCS, vol. 7, no. 2, pp. 98-79, 2015.
[3]http://aws.amazon.com/ec2
[4]http://aws.amazon.com/s3
[5]http://stackoverflow.com/questions/16820336/what-is-saas-paas-and-iaas-with-examples
[6]https://en.wikipedia.org/wiki/Microsoft_Dynamics
[7]S. Kaur and A. Verma, “An efficient approach to genetic algorithm for task scheduling in cloud computing environment”, I.J. Information Technology and Computer Science, 2012, 10, 74-79.
[8]H. Arabnejad, "List based task scheduling algorithms on heterogeneous systems - an overview", http://paginas.fe.up.pt/̃prodei/dsie12/papers/paper30.pdf, 2011, available Online. Consulted January, 2013.
[9]A. Verma and S. Kaushal, “Cloud Computing Security Issues and Challenges: A Survey”, Proceedings of First International Conference, ACC 2011, Kochi, India, pp. 22-24, July 2011.
[10]M. Singh and A. Verma, “Multiple Workflow Scheduling using Deadline Constrained Particle Swarm Optimization in Cloud Computing”, Panjab University, Chandigarh, India, 2013.(M.E. Thesis)
[11]R. Sakellariou and H. Zhao, “A Hybrid Heuristic for DAG Scheduling on Heterogeneous Systems”, Proceeding of the 18th IPDPS '04, pp. 111–124, April 2004.
[12]E. Ilavarasan and P. Thambidurai, "Low Complexity Performance Effective Task Scheduling Algorithm for Heterogeneous Computing Environments", Journal of Computer Sciences, vol. 3, no. 2, pp. 94 - 103, 2007.
[13]R. Eswari, S. Nickolas, “A Level-wise Priority Based Task Scheduling for Heterogeneous Systems”, IJIET, Vol. 1, No. 5, pp. 371-386, December 2011.
[14]E. Ilavarasan, R. Manoharan, “High Performance And Energy Efficient Task Scheduling Algorithm For Heterogeneous Mobile Computing System”, IJCSIT, Vol. 2, No. 2, pp. 10-27, April 2010.
[15]S. Bharti, A. Chervenak, E. Deelman, G. Mehta, M.-H. Su, K. Vahi, “Characterization of Scientific Workflows”, in proceedings of Third Workshop on Workflows in Support of Large – Scale Science (WORKS), Austin, TX, pp:1 – 10, 17 Nov 2008.
[16]https://confluence.pegasus.isi.edu/display/pegasus/WorkflowGenerator