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BoCB: Performance Benchmarking by Analysing Impacts of Cloud Platforms on Consortium Blockchain

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Knowledge Management and Acquisition for Intelligent Systems (PKAW 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14317))

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Abstract

Consortium blockchain has recently witnessed unprecedented popularity due to its implicit features and potential capabilities. On the other hand, cloud computing has become a mature technology and has reshaped numerous other innovative technologies through its flexible and efficient on-demand computing services. Consortium blockchain's performance issues undermine its wider acceptance but unleashing the cloud’s computing capabilities can help to develop the full potential of blockchain. In other words, cloud technology and blockchain's potential integration can be envisaged as a next-generation information technology, highly characterised by scalable and secure solutions, respectively. In this context, it is important to understand what benefits blockchain gains from cloud integration in terms of performance. This article presents a comprehensive, empirical analysis for an in-depth study of the performance of the blockchain, specifically consortium (but not limited to) implemented on the cloud, ranging from identifying potential performance bottlenecks, to configuring system parameters. Furthermore, this article presents a novel framework for blockchain on cloud benchmarking (BoCB) and implement it by a Hyperledger Fabric application on four different commercial Cloud platforms. The evaluation results of the blockchain performance on heterogeneous cloud platforms can help developers select the best possible configuration and resources to optimise their applications accordingly.

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Authors and Affiliations

  1. College of Sciences and Engineering, University of Tasmania, Hobart, Australia

    Zhiqiang Huang, Saurabh Garg, Wenli Yang, Ankur Lohachab, Muhammad Bilal Amin & Byeong-Ho Kang

Authors
  1. Zhiqiang Huang
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  2. Saurabh Garg
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  3. Wenli Yang
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  4. Ankur Lohachab
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  5. Muhammad Bilal Amin
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  6. Byeong-Ho Kang
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Corresponding author

Correspondence to Zhiqiang Huang .

Editor information

Editors and Affiliations

  1. University of Technology Sydney, Sydney, NSW, Australia

    Shiqing Wu

  2. University of Tasmania, Hobart, TAS, Australia

    Wenli Yang

  3. University of Tasmania, Hobart, TAS, Australia

    Muhammad Bilal Amin

  4. University of Tasmania, Hobart, TAS, Australia

    Byeong-Ho Kang

  5. University of Technology Sydney, Sydney, NSW, Australia

    Guandong Xu

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Huang, Z., Garg, S., Yang, W., Lohachab, A., Amin, M.B., Kang, BH. (2023). BoCB: Performance Benchmarking by Analysing Impacts of Cloud Platforms on Consortium Blockchain. In: Wu, S., Yang, W., Amin, M.B., Kang, BH., Xu, G. (eds) Knowledge Management and Acquisition for Intelligent Systems. PKAW 2023. Lecture Notes in Computer Science(), vol 14317. Springer, Singapore. https://doi.org/10.1007/978-981-99-7855-7_4

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  • DOI: https://doi.org/10.1007/978-981-99-7855-7_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-7854-0

  • Online ISBN: 978-981-99-7855-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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