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A Research of Virtual Machine Resource Scheduling Strategy Based on Cloud Computing

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Computational Intelligence and Intelligent Systems (ISICA 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 575))

Abstract

For the load imbalance of resource scheduling, an algorithm based on improved genetic algorithm is proposed after the research of resource load scheduling model based on Cloud Computing. The algorithm designed the fitness function, which uses the spatial utilization rate, load changes and the weight, selected individual by the Roulette Wheel Method, and optimized the crossover and mutation operations. Experiment results demonstrate that the algorithm not only can accelerate convergence of load balance scheme, but also has less migration time. It provides a new solution for the research of load balance and virtual Machine Resource Scheduling Strategy.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Guangdong College of Science and Technology, Dongguan, 523083, China

    Jun Nie

Authors
  1. Jun Nie
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Corresponding author

Correspondence to Jun Nie .

Editor information

Editors and Affiliations

  1. College of Mathematics and Informatics, The South China Agricultural University, Guangzhou, China

    Kangshun Li

  2. School of Computer Science, Guangzhou University, Guangzhou, China

    Jin Li

  3. School of Computer Science and Engineeri, The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Yong Liu

  4. Dept. of Informatics, University of Salerno, Fisciano, Italy

    Aniello Castiglione

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Nie, J. (2016). A Research of Virtual Machine Resource Scheduling Strategy Based on Cloud Computing. In: Li, K., Li, J., Liu, Y., Castiglione, A. (eds) Computational Intelligence and Intelligent Systems. ISICA 2015. Communications in Computer and Information Science, vol 575. Springer, Singapore. https://doi.org/10.1007/978-981-10-0356-1_30

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  • DOI: https://doi.org/10.1007/978-981-10-0356-1_30

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0355-4

  • Online ISBN: 978-981-10-0356-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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