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Dynamic Allocation of Virtual Resources Based on Genetic Algorithm in the Cloud

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Advances in Services Computing (APSCC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9464))

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Abstract

Cloud computing provides dynamic resource allocation using virtualization technology to greatly improve resource efficiency. However, current resource reallocation solution seldom considers the stability of VM placement pattern. Varied workloads of applications would lead to frequent resource reconfiguration requirements due to repeated occurrence of hot nodes. In this paper, a multi-objective genetic algorithm (MOGA) is presented to significantly improve the stability of VM placement pattern with less migration overhead. The group encoding scheme is employed in MOGA to express the mapping of physical nodes and virtual machines (VMs). Fitness function is designed based on the stability and migration overhead of group. Our simulation results demonstrate that, our MOGA is much more efficient than other algorithms for resource reallocation with good stability.

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Acknowledgment

This research was funded by Natural Science Foundation of Hubei Province (No. 2014CFB817), China.

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Authors and Affiliations

  1. College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430065, China

    Li Deng & Li Yao

  2. Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan, 430065, China

    Li Deng

Authors
  1. Li Deng
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  2. Li Yao
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Corresponding author

Correspondence to Li Deng .

Editor information

Editors and Affiliations

  1. School of Computer Sci,Level 4, University of Adelaide, Adelaide, South Australia, Australia

    Lina Yao

  2. School of Computer Cience & Technol, Huazhong University of Science &, Wuhan, China

    Xia Xie

  3. School of Software Technology, Dalian University of Technology, Dalian, China

    Qingchen Zhang

  4. Department of Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, Canada

    Laurence T. Yang

  5. School of Information Technologies, University of Sydney, Sydney, New South Wales, Australia

    Albert Y. Zomaya

  6. School of Comp. Science and Technology, Huazhong Univ. of Science and Technology, Wuhan, China

    Hai Jin

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Deng, L., Yao, L. (2015). Dynamic Allocation of Virtual Resources Based on Genetic Algorithm in the Cloud. In: Yao, L., Xie, X., Zhang, Q., Yang, L., Zomaya, A., Jin, H. (eds) Advances in Services Computing. APSCC 2015. Lecture Notes in Computer Science(), vol 9464. Springer, Cham. https://doi.org/10.1007/978-3-319-26979-5_11

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  • DOI: https://doi.org/10.1007/978-3-319-26979-5_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26978-8

  • Online ISBN: 978-3-319-26979-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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