TY - GEN
T1 - Accelerating BFT Database with Transaction Reconstruction
AU - Kida, Aoi
AU - Kawashima, Hideyuki
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Data stores utilized in modern data-intensive applications are expected to demonstrate rapid read and write capabilities and robust fault tolerance. Byzantine fault-tolerant database (BFT database) can execute transactions concurrently and tolerate arbitrary faults (Byzantine fault). We consider cryptographic and communication processing as performance bottlenecks in the transaction processing of BFT databases. This paper presents a transaction reconstruction method, re-constructing a single transaction from multiple transactions to streamline cryptographic and communication processes. We evaluated the proposed method with Basil (state-of-the-art BFT database) in experiments. In an environment where nodes are geographically centralized, the proposed method demonstrates up to approximately 2.5 times higher throughput and reduces latency by up to about 30% than vanilla Basil. In an environment where nodes are geographically distributed, the proposed method demonstrates up to approximately 50 times higher throughput and reduces latency by up to about 75% than vanilla Basil.
AB - Data stores utilized in modern data-intensive applications are expected to demonstrate rapid read and write capabilities and robust fault tolerance. Byzantine fault-tolerant database (BFT database) can execute transactions concurrently and tolerate arbitrary faults (Byzantine fault). We consider cryptographic and communication processing as performance bottlenecks in the transaction processing of BFT databases. This paper presents a transaction reconstruction method, re-constructing a single transaction from multiple transactions to streamline cryptographic and communication processes. We evaluated the proposed method with Basil (state-of-the-art BFT database) in experiments. In an environment where nodes are geographically centralized, the proposed method demonstrates up to approximately 2.5 times higher throughput and reduces latency by up to about 30% than vanilla Basil. In an environment where nodes are geographically distributed, the proposed method demonstrates up to approximately 50 times higher throughput and reduces latency by up to about 75% than vanilla Basil.
KW - Byzantine fault tolerance
KW - Distributed database
KW - Transaction processing
UR - https://www.scopus.com/pages/publications/85200785705
UR - https://www.scopus.com/pages/publications/85200785705#tab=citedBy
U2 - 10.1109/IPDPSW63119.2024.00061
DO - 10.1109/IPDPSW63119.2024.00061
M3 - Conference contribution
AN - SCOPUS:85200785705
T3 - 2024 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2024
SP - 232
EP - 241
BT - 2024 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2024
Y2 - 27 May 2024 through 31 May 2024
ER -