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Research on Job Scheduling Algorithms Based on Cloud Computing

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Green, Pervasive, and Cloud Computing (GPC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12398))

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Abstract

With the rapid development of digital technology, from the application of traditional databases and scientific computing to the emerging cloud computing services, the analysis and processing of massive data has become the focus of society. Providing low-cost, scalable, and configurable shared cloud services to users on cloud service platforms is a new hotspot for the development of major cloud service providers. Job scheduling plays an important role in improving the overall system performance of cloud service capabilities. Simple job scheduling strategies (such as Fair and FIFO scheduling) do not consider job size and may degrade performance when jobs of different sizes arrive. This paper proposes the MQWAG (Multi-queue Load-Sensitive Greedy Scheduling Algorithm) job scheduling algorithm to reorder multi-queue jobs so that short jobs are executed preferentially in multiple queues. In our experiments, our algorithm shortened the average job completion time by about 26% compared with other algorithms.

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Acknowledgments

The work is partially supported by The 2019 Xinjiang Uygur Autonomous Region Higher Education Scientific Research Project (XJEDU2019Y057,XJEDU2019Y049).

Author information

Authors and Affiliations

  1. Changji College, Changji, 831100, China

    Gang Qiu & Yang Gao

  2. Shandong University, Jinan, 250100, China

    Gang Qiu & Yajun Zhang

  3. Xinjiang University, Urumqi, 830046, China

    Yajun Zhang

Authors
  1. Gang Qiu
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  2. Yang Gao
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  3. Yajun Zhang
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Corresponding author

Correspondence to Yajun Zhang .

Editor information

Editors and Affiliations

  1. Northwestern Polytechnical University, Xi’an, China

    Zhiwen Yu

  2. University of Mannheim, Mannheim, Germany

    Christian Becker

  3. Chinese University of Hong Kong, Shatin, Hong Kong

    Guoliang Xing

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Qiu, G., Gao, Y., Zhang, Y. (2020). Research on Job Scheduling Algorithms Based on Cloud Computing. In: Yu, Z., Becker, C., Xing, G. (eds) Green, Pervasive, and Cloud Computing. GPC 2020. Lecture Notes in Computer Science(), vol 12398. Springer, Cham. https://doi.org/10.1007/978-3-030-64243-3_36

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  • DOI: https://doi.org/10.1007/978-3-030-64243-3_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64242-6

  • Online ISBN: 978-3-030-64243-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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