TY - GEN
T1 - Time-Sensitive Data Processing Strategy for Enhancing the Performance of BFT Consensus Mechanism in IoT Edge Computing Environment
AU - Qian, Cheng
AU - Tang, Wenzhong
AU - Wang, Yanyang
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/9/15
Y1 - 2023/9/15
N2 - Applying the BFT consensus mechanism in the IoT edge computing environment effectively solves the problem of data consistency and trustworthiness. However, the existing BFT consensus mechanism needs to pay attention to the impact of the data processing flow on consensus performance, and the repetitive data processing operations lead to the waste of computing resources of consensus nodes. Therefore, in this paper, we analyze the data processing flow of the BFT consensus mechanism, propose a time-sensitive data processing strategy from the idea of reducing the number of consensus nodes involved in data processing, and select data processing nodes by taking data processing time as the optimization target to improve the resource utilization of consensus nodes while ensuring consensus reaching. Through simulation experiments, our proposed time-sensitive data processing strategy achieves the best latency and throughput performance in a simulated IoT edge computing environment, demonstrating that the time-sensitive data processing strategy can effectively improve the performance of the BFT consensus mechanism.
AB - Applying the BFT consensus mechanism in the IoT edge computing environment effectively solves the problem of data consistency and trustworthiness. However, the existing BFT consensus mechanism needs to pay attention to the impact of the data processing flow on consensus performance, and the repetitive data processing operations lead to the waste of computing resources of consensus nodes. Therefore, in this paper, we analyze the data processing flow of the BFT consensus mechanism, propose a time-sensitive data processing strategy from the idea of reducing the number of consensus nodes involved in data processing, and select data processing nodes by taking data processing time as the optimization target to improve the resource utilization of consensus nodes while ensuring consensus reaching. Through simulation experiments, our proposed time-sensitive data processing strategy achieves the best latency and throughput performance in a simulated IoT edge computing environment, demonstrating that the time-sensitive data processing strategy can effectively improve the performance of the BFT consensus mechanism.
KW - BFT consensus mechanism
KW - Blockchain
KW - Data processing strategy
KW - Edge computing
KW - Internet of things
UR - https://www.scopus.com/pages/publications/85180158933
U2 - 10.1145/3625403.3625436
DO - 10.1145/3625403.3625436
M3 - 会议稿件
AN - SCOPUS:85180158933
T3 - ACM International Conference Proceeding Series
SP - 181
EP - 188
BT - 2023 2nd International Conference on Algorithms, Data Mining, and Information Technology, ADMIT 2023 - Conference Proceedings
PB - Association for Computing Machinery
T2 - 2nd International Conference on Algorithms, Data Mining, and Information Technology, ADMIT 2023
Y2 - 15 September 2023 through 17 September 2023
ER -