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Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment

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  • Syed Hamid Hussain Madni
  • Muhammad Shafie Abd Latiff
  • Mohammed Abdullahi
  • Shafi’i Muhammad Abdulhamid
  • Mohammed Joda Usman

Abstract

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing.

Suggested Citation

  • Syed Hamid Hussain Madni & Muhammad Shafie Abd Latiff & Mohammed Abdullahi & Shafi’i Muhammad Abdulhamid & Mohammed Joda Usman, 2017. "Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-26, May.
    • Handle: RePEc:plo:pone00:0176321
    DOI: 10.1371/journal.pone.0176321
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    References listed on IDEAS

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    1. Shafi’i Muhammad Abdulhamid & Muhammad Shafie Abd Latiff & Gaddafi Abdul-Salaam & Syed Hamid Hussain Madni, 2016. "Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-18, July.
    2. Mohammed Abdullahi & Md Asri Ngadi, 2016. "Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-29, June.
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    Cited by:

    1. Mor Harchol-Balter, 2021. "Open problems in queueing theory inspired by datacenter computing," Queueing Systems: Theory and Applications, Springer, vol. 97(1), pages 3-37, February.

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