Exploring the Characteristics of Hyperledger Fabric in Resource Consumption

Jeongsu Kim, Kyungwoon Lee, Gyeongsik Yang, Kwanhoon Lee, Jaemin Im, Chuck Yoo

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    As blockchain applications are available in clouds, the resource allocation of blockchain becomes an important issue. This paper investigates the resource consumption of Hyperledger Fabric that is a popular blockchain framework. As Fabric consists of several components, this paper characterizes the resource consumption of Fabric components. Then, we attempt to control the CPU allocation of the components and explore the performance implications. Our evaluation results show that the 'proper' CPU allocation of Kafka component reduces the CPU usage of the overall Fabric by 14% but the performance of Fabric does not decrease. Our result suggests that clouds can benefit from such control of CPU allocation to Fabric.

    Original languageEnglish
    Title of host publication2020 2nd Conference on Blockchain Research and Applications for Innovative Networks and Services, BRAINS 2020
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages208-209
    Number of pages2
    ISBN (Electronic)9781728170916
    DOIs
    Publication statusPublished - 2020 Sept
    Event2nd Conference on Blockchain Research and Applications for Innovative Networks and Services, BRAINS 2020 - Paris, France
    Duration: 2020 Sept 282020 Sept 30

    Publication series

    Name2020 2nd Conference on Blockchain Research and Applications for Innovative Networks and Services, BRAINS 2020

    Conference

    Conference2nd Conference on Blockchain Research and Applications for Innovative Networks and Services, BRAINS 2020
    Country/TerritoryFrance
    CityParis
    Period20/9/2820/9/30

    Bibliographical note

    Publisher Copyright:
    © 2020 IEEE.

    Keywords

    • Blockchain
    • Hyperledger Fabric
    • Performance
    • Resource allocation
    • Resource consumption

    ASJC Scopus subject areas

    • Management Information Systems
    • Artificial Intelligence
    • Computer Networks and Communications
    • Decision Sciences (miscellaneous)
    • Information Systems and Management

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