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Research on Task Allocation and Resource Scheduling Method in Cloud Environment

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Advances in Intelligent Systems and Interactive Applications (IISA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1084))

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Abstract

Task allocation and resource scheduling capability are important indicators for evaluating cloud environment. Aiming at the problems of low resource utilization, high algorithm time complexity and low task allocation efficiency of existing task allocation strategies, a task allocation and resource scheduling method based on dynamic programming in cloud environment is proposed. Using the idea of dynamic programming, this method regards the matching of tasks and servers as a combination of multi-stage decision-making, and obtains the optimization scheme of task allocation, which reduces the completion time of tasks. The experimental results show that the proposed method can reduce the task completion time and the resource load is relatively balanced, which can effectively improve the task execution efficiency.

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Acknowlegements

The work of this paper is funded by the project of National Key Research and Development Program of China (No. 2016YFB0800802, No. 2017YFB0801804), Frontier Science and Technology Innovation of China (No. 2016QY05X1002-2), National Regional Innovation Center Science and Technology Special Project of China (No. 2017QYCX14), Key Research and Development Program of Shandong Province (No. 2017CXGC0706), and University Co-construction Project in Weihai City.

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Authors and Affiliations

  1. Harbin Institute of Technology, Harbin, China

    Pengpeng Wang, Kaikun Dong, Hongri Liu, Bailing Wang & Wei Wang

  2. Harbin University of Technology (Weihai) Innovation Pioneer Park Co. Ltd., Harbin, China

    Bailing Wang

  3. Qilu University of Technology (Shandong Academy of Science), Jinan, China

    Lianhai Wang

  4. Luoyang Electronic Equipment Test Centre of China, Luoyang, China

    Pengpeng Wang

Authors
  1. Pengpeng Wang
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  2. Kaikun Dong
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  3. Hongri Liu
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  4. Bailing Wang
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  5. Wei Wang
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  6. Lianhai Wang
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Corresponding author

Correspondence to Wei Wang .

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Editors and Affiliations

  1. Dept De Ciències De La Computació, Universitat Politècnica De Catalunya, Barcelona, Spain

    Fatos Xhafa

  2. Department of Computer Science and Engineering, SOA University, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  3. Department of Business Systems and Analytics, La Salle University, Philadelphia, PA, USA

    Madjid Tavana

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Wang, P., Dong, K., Liu, H., Wang, B., Wang, W., Wang, L. (2020). Research on Task Allocation and Resource Scheduling Method in Cloud Environment. In: Xhafa, F., Patnaik, S., Tavana, M. (eds) Advances in Intelligent Systems and Interactive Applications. IISA 2019. Advances in Intelligent Systems and Computing, vol 1084. Springer, Cham. https://doi.org/10.1007/978-3-030-34387-3_69

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