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原文摘要

Smart contracts have turned blockchains into general platforms, and their throughput is increasingly limited by transaction execution. Parallel execution can relieve this bottleneck. However, most existing engines apply a single policy within a block, typically optimistic (OCC) or pessimistic (PCC) concurrency control, and thus re-execute or delay whole transactions. Although some database studies have proposed hybrid and adaptive mechanisms, these mechanisms cannot be applied directly to blockchains because the block fixes the serial order, accesses emerge only at run time, and real workloads vary widely. We propose RegionFence, an adaptive concurrency control mechanism for blockchain parallel transaction execution, based on three key designs. First, we propose regions to refine the granularity of control from whole transactions to the parts that touch contended keys. Second, we design fences to decide at run time how each region handles a conflict. Third, we introduce intra-block and inter-block online learning to anticipate likely conflicts. At the same time, the system still produces the same result as serial execution in consensus order. We implement RegionFence in go-ethereum and evaluate it on real Ethereum mainnet blocks from different periods of the past five years. Experimental results show that RegionFence achieves an overall speedup of 9.2x over single-core execution on 64 cores and outperforms OCC by 2.9-5.4x and PCC by 3.9-9.4x in speedup across these periods.