| DOI | Resolve DOI: https://doi.org/10.1109/DASC-PICom-CBDCom-CyberSciTech52372.2021.00023 |
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| Author | Search for: Sondhi, Shiv; Search for: Saad, Sherif; Search for: Shi, Kevin; Search for: Mamun, Mohammad1; Search for: Traore, Issa |
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| Affiliation | - National Research Council of Canada. Digital Technologies
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| Funder | Search for: University of Windsor |
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| Format | Text, Article |
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| Conference | 2021 IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing, International Conference on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech), October 25-28, 2021, AB, Canada |
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| Subject | chaos; distributed ledger; calability; system performance; consensus algorithm; production; throughput |
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| Abstract | A critical component of any blockchain or distributed ledger technology (DLT) platform is the consensus algorithm. Blockchain consensus algorithms are the primary vehicle for the nodes within a blockchain network to reach an agreement. In recent years, many blockchain consensus algorithms have been proposed mainly for private and permissioned blockchain networks. However, the performance of these algorithms and their reliability in hostile environments or the presence of byzantine and other network failures are not well understood. In addition, the testing and validation of blockchain applications come with many technical challenges. In this paper, we apply chaos engineering and testing to understand the performance of consensus algorithms in the presence of different loads, byzantine failure and other communication failure scenarios. We apply chaos engineering to evaluate the performance of three different consensus algorithms (PBFT, Clique, Raft) and their respective blockchain platforms. We measure the blockchain network's throughput, latency, and success rate while executing chaos and load tests. We develop lightweight blockchain applications to execute our test in a semi-production environment. Our results show that using chaos engineering helps understand how different consensus algorithms perform in a hostile or unreliable environment and the limitations of blockchain platforms. Our work demonstrates the benefits of using chaos engineering in testing complex distributed systems such as blockchain networks. |
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| Publication date | 2021-10-25 |
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| Publisher | IEEE |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 56e35f97-945d-44eb-b463-b4a8e2c072ef |
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| Record created | 2022-09-29 |
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| Record modified | 2022-09-29 |
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