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International Conference on Internet of Vehicles

IOV 2016: Internet of Vehicles – Technologies and Services pp 225–231Cite as

Performance Evaluation for Traditional Virtual Machine Placement Algorithms in the Cloud

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10036))

Abstract

The virtual machine placement problem can be described as designing optimal placement scheme for virtual machine in cloud environment. Cloud data centers are facing increasingly virtual machine placement problems, such as high energy consumption, imbalanced utilization of multidimensional resource, and high resource wastage rate. In this paper, typical exact and heuristic algorithms as solution to the virtual machine placement problem in the cloud are surveyed in terms of energy consumption and resource wastage. The purpose of this paper is to evaluate the performance of both the exact and approximate algorithms developed by using the WebCloudSim sytem.

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Author information

Authors and Affiliations

  1. Beijing University of Posts and Telecommunications, Beijing, China

    Ruo Bao

Authors
  1. Ruo Bao
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Corresponding author

Correspondence to Ruo Bao .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Chung Hua University, Hsinchu, Taiwan, Taiwan

    Ching-Hsien Hsu

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Shangguang Wang

  3. Beijing University of Posts and Telecommunications, Beijing, China

    Ao Zhou

  4. The University of Fiji, Suva, Fiji

    Ali Shawkat

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© 2016 Springer International Publishing AG

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Bao, R. (2016). Performance Evaluation for Traditional Virtual Machine Placement Algorithms in the Cloud. In: Hsu, CH., Wang, S., Zhou, A., Shawkat, A. (eds) Internet of Vehicles – Technologies and Services. IOV 2016. Lecture Notes in Computer Science(), vol 10036. Springer, Cham. https://doi.org/10.1007/978-3-319-51969-2_19

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  • DOI: https://doi.org/10.1007/978-3-319-51969-2_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51968-5

  • Online ISBN: 978-3-319-51969-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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