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Optimized Consensus Group Selection Focused on Node Transmission Delay in Sharding Blockchains

delete2025-06-01
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PRE
AI
L
Liping Tao
Y
Yang Lu
樊玉琦 (Yuqi Fan)
C
Chee Wei Tan
Z
Zhen Wei
DOI:10.1109/TCSS.2024.3514186delete
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Abstract

Abstract

En 中文
Sharding presents an enticing path toward improving blockchain scalability. However, the consensus mechanism within individual shards faces mounting security challenges due to the restricted number of consensus nodes and the reliance on conventional, unchanging nodes for consensus. Common strategies to enhance shard consensus security often involve increasing the number of consensus nodes per shard. While effective in bolstering security, this approach also leads to a notable rise in consensus delay within each shard, potentially offsetting the scalability advantages of sharding. Hence, it becomes imperative to strategically select nodes to form dedicated consensus groups for each shard. These groups should not only enhance shard consensus security but also do so without exacerbating consensus delay. In this article, we propose a novel consensus group selection based on transmission delay between nodes (CGSTD) to address this challenge, with the goal of minimizing the overall consensus delay across the system. CGSTD intelligently selects nodes from various shards to form distinct consensus groups for each shard, thereby enhancing shard security while maintaining optimal system-wide consensus efficiency. We conduct a rigorous theoretical analysis to evaluate the security properties of CGSTD and derive approximation ratios under various operational scenarios. Simulation results validate the superior performance of CGSTD compared to baseline algorithms, showcasing reductions in total consensus delay, mitigated increases in shard-specific delay, optimized block storage utilization per node, and streamlined participation of nodes in consensus groups.
Keywords:
Consensus optimization
distributed system
scalability
security
sharding blockchain

Journal

IEEE Transactions on Computational Social Systems cover
IEEE Transactions on Computational Social Systems
IF:
4.9
Papers:
577
Citations:
6.8K

Organization

H
hefei university of technology
Scholars:
2.5W
Papers: 1.7W
Citations: 35
N
Nanyang Technological University
Scholars:
4.9W
Papers: 4.8W
Citations: 8.1W