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Fabric-Visualizer: A Transaction Dependency Visualizer for Hyperledger Fabric

Published: 11 December 2023 Publication History

Abstract

Hyperledger Fabric is a popular permissioned blockchain that follows an optimistic concurrency control model, which often leads to transaction dependency conflicts. We developed a web application that extracts data from a live Fabric network and generates transaction dependency graphs. Apart from visually understanding the transaction dependency distribution, the user also gets additional information regarding each transaction, such as the validation status, dependent transactions, smart contract function, accessed keys, endorsers and clients. Further, our tool also checks the serializability of the generated graph and identifies the number of transactions to abort to achieve serializability. We demonstrate how our tool can be used with multiple realistic workloads to identify performance optimization opportunities. We also highlight scenarios where our tool can be used to identify smart contract improvements. Our tool is demonstrated with multiple realistic workloads.

References

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Jeeta Ann Chacko, Ruben Mayer, and Hans-Arno Jacobsen. 2021. Why Do My Blockchain Transactions Fail? A Study of Hyperledger Fabric. In Proceedings of the 2021 International Conference on Management of Data (Virtual Event, China) (SIGMOD/PODS '21). Association for Computing Machinery.
[2]
Jeeta Ann Chacko, Ruben Mayer, and Hans-Arno Jacobsen. 2023. How To Optimize My Blockchain? A Multi-Level Recommendation Approach. Proc. ACM Manag. Data 1, 1, Article 24 (may 2023). https://doi.org/10.1145/3588704
[3]
Androulaki et al. 2018. Hyperledger Fabric: A Distributed Operating System for Permissioned Blockchains. In Proceedings of the Thirteenth EuroSys Conference (Porto, Portugal) (EuroSys '18). ACM, Article 30, 30:1--30:15 pages.
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Michel Rauchs, Apolline Blandin, Keith Bear, and Stephen B McKeon. 2019. 2nd global enterprise blockchain benchmarking study. Available at SSRN 3461765 (2019).
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Pingcheng Ruan, Dumitrel Loghin, Quang-Trung Ta, Meihui Zhang, Gang Chen, and Beng Chin Ooi. 2020. A Transactional Perspective on Execute-Order-Validate Blockchains. In Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data (Portland, OR, USA) (SIGMOD '20). https://doi.Org/10.l 145/3318464.3389693
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Ankur Sharma, Felix Martin Schuhknecht, Divya Agrawal, and Jens Dittrich. 2019. Blurring the Lines Between Blockchains and Database Systems: The Case of Hyperledger Fabric. In Proceedings of the 2019 International Conference on Management of Data (Amsterdam, Netherlands) (SIGMOD '19). ACM, New York, NY, USA, 105--122. https://doi.org/10.1145/3299869.3319883
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Shenbin Zhang, Ence Zhou, Bingfeng Pi, Jun Sun, Kazuhiro Yamashita, and Yoshihide Nomura. 2019. A Solution for the Risk of Non-deterministic Transactions in Hyperledger Fabric. 2019 IEEE International Conference on Blockchain and Cryptocurrency (ICBC) (2019), 253--261.

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  1. Fabric-Visualizer: A Transaction Dependency Visualizer for Hyperledger Fabric

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    cover image ACM Conferences
    Middleware '23: Proceedings of the 24th International Middleware Conference: Demos, Posters and Doctoral Symposium
    December 2023
    41 pages
    ISBN:9798400704291
    DOI:10.1145/3626564
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    New York, NY, United States

    Publication History

    Published: 11 December 2023

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    Author Tags

    1. blockchains
    2. hyperledger fabric
    3. transaction dependency

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    • Short-paper
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    • Refereed limited

    Funding Sources

    • Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)
    • Bavarian Cooperative Research Program of the Free State of Bavaria

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    Middleware '23
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    Overall Acceptance Rate 203 of 948 submissions, 21%

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