Enhanced Practical Byzantine Fault Tolerance via Dynamic Hierarchy Management and Location-Based Clustering

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Abstract

Blockchain is a distributed database technology that operates in a P2P network and is used in various domains. Depending on its structure, blockchain can be classified into types such as public and private. A consensus algorithm is essential in blockchain, and various consensus algorithms have been applied. In particular, a non-competitive consensus algorithm called PBFT is mainly used in private blockchains. However, there are limitations to scalability. This paper proposes an enhanced PBFT with dynamic hierarchy management and location-based clustering to overcome these problems. The proposed method clusters nodes based on location information and adjusts the dynamic hierarchy to optimize consensus latency. As a result of the experiment, the proposed PBFT showed significant performance improvement compared to the existing typical PBFT and Dynamic Layer Management PBFT (DLM-PBFT). The proposed PBFT method showed a processing performance improvement rate of approximately 107% to 128% compared to PBFT, and 11% to 99% compared to DLM-PBFT.

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Kim, G., Cho, J., Choi, M., & Kim, B. (2024). Enhanced Practical Byzantine Fault Tolerance via Dynamic Hierarchy Management and Location-Based Clustering. Sensors, 24(1). https://doi.org/10.3390/s24010060

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