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An Automatic Deployment Method for Hybrid Cloud Simulation Platform

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Advanced Parallel Processing Technologies (APPT 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14103))

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Abstract

The simulation resources are now virtualized and deployed on cloud platform. It can provide on-demand simulation tests, improving the efficiency of simulation systems. Simulation resources are packaged into virtual machines or containers. Complex software are packaged into virtual machines, and simple simulation services are packaged into containers. However, how to deploy simulation systems under resource constraints is a problem worth studying. This paper studies a virtual machine and container based hybrid cloud simulation platform. An automatic deployment method is proposed to reduce labor costs and errors of manual deployment. A simulation case is applied to verify the usefulness and efficiency of our approach.

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Author information

Authors and Affiliations

  1. Beijing Institute of Technology, Beijing, China

    Xilai Yao, Yizhuo Wang & Weixing Ji

  2. Beijing Simulation Center, Beijing, China

    Qiurui Chen

Authors
  1. Xilai Yao
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  2. Yizhuo Wang
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  3. Weixing Ji
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  4. Qiurui Chen
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Corresponding author

Correspondence to Xilai Yao .

Editor information

Editors and Affiliations

  1. Shanghai Jiao Tong University, Shanghai, China

    Chao Li

  2. Tsinghua University, Beijing, Beijing, China

    Zhenhua Li

  3. National University of Defense Technology, Nanjing, China

    Li Shen

  4. Shanghai Jiao Tong University, Shanghai, China

    Fan Wu

  5. Nankai University, Tianjin, China

    Xiaoli Gong

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Yao, X., Wang, Y., Ji, W., Chen, Q. (2024). An Automatic Deployment Method for Hybrid Cloud Simulation Platform. In: Li, C., Li, Z., Shen, L., Wu, F., Gong, X. (eds) Advanced Parallel Processing Technologies. APPT 2023. Lecture Notes in Computer Science, vol 14103. Springer, Singapore. https://doi.org/10.1007/978-981-99-7872-4_10

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  • DOI: https://doi.org/10.1007/978-981-99-7872-4_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-7871-7

  • Online ISBN: 978-981-99-7872-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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