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Optimized Cost-Based Biomedical Workflow Scheduling Algorithm in Cloud

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Advances in Signal Processing and Intelligent Recognition Systems (SIRS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 678))

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Abstract

Owing to the data deluge of biomedical workflow applications, researchers consider cloud as a promising environment for deploying biomedical workflow applications. As the Workflow applications consist of precedence-constrained tasks, it requires high computing resources for its execution. Scheduling of pertinent resource to biomedical workflow applications is an appealing research area. The key concern is that the workflow applications should be scheduled with the appropriate resource such that the overall execution time and cost would be minimized and correspondingly resource utilization is maximized. The proposed Optimized Cost Scheduling Algorithm (OCSA) addresses this issue by scheduling the workflows to a resource in such a way that it efficiently reduces the time and cost. The proposed OCSA algorithm is simulated rigorously in WorkflowSim on real biomedical workflow application and the results are compared with the existing workflow scheduling approaches in terms of cost and time. The simulation result shows that the proposed scheduling algorithm appreciably reduces the execution time and cost than the existing scheduling algorithms.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Coimbatore Institute of Technology, Coimbatore, India

    N. Mohanapriya & G. Kousalya

Authors
  1. N. Mohanapriya
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  2. G. Kousalya
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Corresponding author

Correspondence to N. Mohanapriya .

Editor information

Editors and Affiliations

  1. School of CS/IT, Indian Institute of Information Technology and Management, Trivandrum, Kerala, India

    Sabu M. Thampi

  2. Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada

    Sri Krishnan

  3. Department of Computer Science, University of Salamanca, Salamanca, Salamanca, Spain

    Juan Manuel Corchado Rodriguez

  4. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

  5. Department of Systems and Computer Networks, Wroclaw University of Science and Technology, Wroclaw, Poland

    Michal Wozniak

  6. Faculty of Engineering and Technology, Liverpool John Moores University, Liverpool, United Kingdom

    Dhiya Al-Jumeily

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Mohanapriya, N., Kousalya, G. (2018). Optimized Cost-Based Biomedical Workflow Scheduling Algorithm in Cloud. In: Thampi, S., Krishnan, S., Corchado Rodriguez, J., Das, S., Wozniak, M., Al-Jumeily, D. (eds) Advances in Signal Processing and Intelligent Recognition Systems. SIRS 2017. Advances in Intelligent Systems and Computing, vol 678. Springer, Cham. https://doi.org/10.1007/978-3-319-67934-1_40

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  • DOI: https://doi.org/10.1007/978-3-319-67934-1_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67933-4

  • Online ISBN: 978-3-319-67934-1

  • eBook Packages: EngineeringEngineering (R0)

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