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Batch Auction Design for Cloud Container Services

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Quality, Reliability, Security and Robustness in Heterogeneous Systems (QShine 2019)

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Abstract

Cloud containers represent a new, light-weight alternative to virtual machines in cloud computing. A user job may be described by a container graph that specifies the resource profile of each container and container dependence relations. This work is the first in the cloud computing literature that designs efficient market mechanisms for container based cloud jobs. Our design targets simultaneously incentive compatibility, computational efficiency, and economic efficiency. It further adapts the idea of batch online optimization into the paradigm of mechanism design, leveraging agile creation of cloud containers and exploiting delay tolerance of elastic cloud jobs. The new and classic techniques we employ include: (i) compact exponential optimization for expressing and handling non-traditional constraints that arise from container dependence and job deadlines; (ii) the primal-dual schema for designing efficient approximation algorithms for social welfare maximization; and (iii) posted price mechanisms for batch decision making and truthful payment design. Theoretical analysis and trace-driven empirical evaluation verify the efficacy of our container auction algorithms.

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Author information

Authors and Affiliations

  1. School of Computer Science, Wuhan University, Wuhan, China

    Yu He, Lin Ma & Chuanhe Huang

  2. School of Cyber Science and Engineering, Wuhan University, Wuhan, China

    Ruiting Zhou

Authors
  1. Yu He
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  2. Lin Ma
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  3. Ruiting Zhou
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  4. Chuanhe Huang
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Corresponding author

Correspondence to Ruiting Zhou .

Editor information

Editors and Affiliations

  1. Hong Kong Baptist University, Hong Kong, China

    Xiaowen Chu

  2. Hunan University, Hunan, China

    Hongbo Jiang

  3. The Hong Kong University of Science and Technology, Hong Kong, China

    Bo Li

  4. The Hong Kong Polytechnic University, Hong Kong, China

    Dan Wang

  5. The Hong Kong University of Science and Technology, Hong Kong, China

    Wei Wang

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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He, Y., Ma, L., Zhou, R., Huang, C. (2020). Batch Auction Design for Cloud Container Services. In: Chu, X., Jiang, H., Li, B., Wang, D., Wang, W. (eds) Quality, Reliability, Security and Robustness in Heterogeneous Systems. QShine 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 300. Springer, Cham. https://doi.org/10.1007/978-3-030-38819-5_8

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  • DOI: https://doi.org/10.1007/978-3-030-38819-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-38818-8

  • Online ISBN: 978-3-030-38819-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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