FabricXF: A Lightweight Inter-block Conflict Detection and Parallel Validation Framework for Hyperledger Fabric Based on XORFilter

In high-concurrency settings, Hyperledger Fabric often experiences transaction validation failures due to read-write conflicts, especially from unmodeled inter-block dependencies. This issue seriously affects system throughput and resource efficiency. While most existing research focuses on optimizing transaction ordering within single blocks, inter-block conflicts remain under-addressed. To solve this, we propose FabricXF, an inter-block conflict detection and parallel validation framework based on XORFilter. FabricXF creates lightweight filters for each block to record write-set keys, enabling quick identification of potential read-write conflicts during block construction and validation. It also introduces a block-level parallel validation model that allows concurrent validation of multiple blocks when there are no data dependencies, removing the serial bottleneck in the validation phase. Experiments show that FabricXF greatly boosts system throughput, lowers validation failure rates, and keeps a very low false-positive rate and memory footprint across various concurrent transaction scenarios.

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Published
2025-05-09
DOI
https://doi.org/10.1109/cisce65916.2025.11065356
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

FabricXF: A Lightweight Inter-block Conflict Detection and Parallel Validation Framework for Hyperledger Fabric Based on XORFilter

Wenhao Zhu, Shaqi Fu, Liang Ye, Ying Li
Industrial Vision Systems and Defect Detection
article

FabricXF: A Lightweight Inter-block Conflict Detection and Parallel Validation Framework for Hyperledger Fabric Based on XORFilter

Wenhao Zhu, Shaqi Fu, Liang Ye, Ying Li
article en

Abstract

In high-concurrency settings, Hyperledger Fabric often experiences transaction validation failures due to read-write conflicts, especially from unmodeled inter-block dependencies. This issue seriously affects system throughput and resource efficiency. While most existing research focuses on optimizing transaction ordering within single blocks, inter-block conflicts remain under-addressed. To solve this, we propose FabricXF, an inter-block conflict detection and parallel validation framework based on XORFilter. FabricXF creates lightweight filters for each block to record write-set keys, enabling quick identification of potential read-write conflicts during block construction and validation. It also introduces a block-level parallel validation model that allows concurrent validation of multiple blocks when there are no data dependencies, removing the serial bottleneck in the validation phase. Experiments show that FabricXF greatly boosts system throughput, lowers validation failure rates, and keeps a very low false-positive rate and memory footprint across various concurrent transaction scenarios.

Shanghai University (CN)
National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality
Openalex Percentile: Top 76%
Industrial Vision Systems and Defect Detection
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