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FLUID: Towards Efficient Continuous Transaction Processing in DAG-Based Blockchains

delete2023-12-01
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PRE
AI
肖
肖江 (Jiang Xiao) *
S
Shijie Zhang
B
Bo Li
李葆春 封面图
李葆春 (Baochun Li)
金
金海 (Hai Jin)
DOI:10.1109/TKDE.2023.3272312delete
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摘要

摘要

En 中文
In most blockchain-based application scenarios, a complete application logic consists of multiple continuous transactions, in which the initiation of one transaction depends on the confirmation result of the previous one. This mandates that continuous transactions must be processed in the correct order. Unfortunately, existing chain-based blockchains fail to effectively support continuous transaction processing due to considerable latency in confirming continuous transactions. Recent studies shifted from chain-based blockchains to Directed Acyclic Graph (DAG) based blockchains, which reduced transaction confirmation latencies. However, DAG-based blockchains store transactions in an out-of-order manner that leads to unordered transaction processing. To address this challenge, we propose FLUID, a new DAG-based blockchain that supports continuous transaction processing while delivering high performance. The fundamental idea of FLUID is to design a transaction dependency tracking structure to ensure that continuous transactions can be processed in the correct order. FLUID utilizes a conflict resolution mechanism to provide instant confirmation and to support concurrent transaction processing with lower latencies. In addition, FLUID builds a checkpoint-based verification mechanism to achieve deterministic consensus on transaction processing results in the DAG. Extensive experiments demonstrate that our proposed FLUID can improve the throughput over state-of-the-art OHIE by 66% with two orders of magnitude lower latencies.
Keyword:
Blockchain
continuous transaction processing
DAG
data trading
storage model

期刊

IEEE Transactions on Knowledge and Data Engineering 封面图
IEEE Transactions on Knowledge and Data Engineering
IF:
10.4
论文数:
6.9K
被引数:
3.2W

机构

U
University of Toronto
学者数:
4.7K
论文数: 1.6K
被引数: 0
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